Why Power BI is better than Tableau..??

Power BI and Tableau are the most popular and discussed tool in the Business Intelligence industry. They both have established themselves together of the leaders of the industry. People are still confusing between the two and don’t know which one to use to fulfil their purpose. We, Brillica Services, are here to tell you the pros you will find if you choose Power BI over the Tableau. Both the tools have evolved with time, upgraded and adapted since their existence. ....

Now, lets see the comparison between the 2 and understand what are the benefits we get once we choose Power BI over Tableau:
Pricing:There is no variation between the pricing of the two softwares. Power BI is much cheaper and affordable than Tableau. Keep in mind that this price comparison is given just for individual licenses. Both have different setup and features, so it might be wrong to match both of them generally . These tools are also available in individual and organization versions, with obvious differences in their pricing and facilities.
In the enterprise version, there is a shocking price difference between these two as Tableau’s price simply goes on another level for the enterprise users. License for Tableau is provided as per the user needs whereas Power Bi is provided as a separate package.
Integration advantage over Tableau: Power BI is trusted by Microsoft, so it enjoys inbuilt support of Office 365. It has bundled with Office 365 Enterprise E5 plan, which extends support for other Microsoft products and services which includes Exchange, OneDrive and SharePoint. With this inbuilt support, Power BI enables you to use the pre-existing data and analytics structures available on other Office 365 tools. It is very convincing for shops operated by excel. For the analytical shops, this is often an excellent advantage and success. The only thing to stay in mind here is that the info should be from an equivalent source of Power BI report.
Data manipulation: Converting data into a visual perception is a key feature when it comes to BI tools. Power BI have many other ways of manipulating data, whether it is by generating a report, extracting data via an API or some data modelling. If you manipulate data within Power BI, it's in no time and efficient.
As concerning, Power BI is additionally a really influential tool as compared as here you are doing not got to connect Hadoop together with your application unlike Tableau. Small databases can work here too.
The counterpart Tableau offers to convert the data into comprehensible insights with gripping graphics. It is as easy as clicking fingers to make an ad-hoc report from the dashboard.
Power BI vs Tableau security features: As we know, Microsoft takes security breaches very seriously and keeps on patching and updating all its products. The same is the case with the security of Power BI. All the safety protocols and submission needs are checked and followed at the very best level. As a pacesetter of knowledge security, Microsoft keeps investing and expanding on security research. Comparatively, Tableau is nowhere near in terms of privacy and security and doesn't put into the safety aspect the maximum amount . It is more popular for the info visualization part.
Customer Support: Just like the Microsoft Power BI paid software, Tableau provides the customer with the routine service. The customer support are going to be valid for a full year from the date of subscription. After that customers will need to pay some nominal support fee if they need to stay availing of the premium customer support feature. Extended support are often availed by the purchasers if they need to.
In comparison, Power BI provides the users with various support channels in comparison to Tableau. Each channel serves its purpose. One of the tasks is to take care of a dynamic support group. This is mentioned because the “Power BI community” users can post queries, answers and find the simplest practices and walkthrough on certain topics on this forum. Power BI community is hospitable Pro and Premium users. It caters to people with technical requirements in conjunction with administrative purpose.
MS 365 administrator centre provides all the users organisation level support. Complaints or queries are generally fixed with the help of a call . Both tools have similar support for patrons and therefore the only major difference is that the paid support that you simply get once you finally plan to purchase the subscription. Apart from that, there is no other visible difference.
ETL/Data Discovery Suite: Power BI features a scalable and robust tool to perform Extract Transform and cargo operation which beats Tableau in every aspect. Data transformation is that the major work that must be done before a report are often generated. This is one inbuilt feature that you don’t got to search for a 3rd party.

Why Python is preferred For Automation?

Besides providing access to check automation tools, the power to know code also advances manual testing, a method or another, it enhances a person’s competencies and makes a software testing company better prepared for the market challenges. The question is what programming language to find out and use for writing tests. Usually, tech specialists face a “Python vs Java” dilemma. ....

What is Python & Why Is It Popular?

Python programming is an open-source programming language. Over 70% of developers consider it the foremost popular and in-demand language. There are many libraries in open access, so there are fewer lines of original code to write down on your own. Python programming syntax is straight forward, making the language easy to find out. Moreover, there's a robust community built around Python, and you'll reach out for help online anytime.

Why Is Learning Python the best Idea?

Nothing speaks of Python programming language better than its rise within the TIOBE index. But the recognition isn’t the sole reason why Quality Assurance companies continue using it. Technologies like Java, C#, C++, and Ruby are often utilized in test automation services. Still, Python programming features a number of advantages that makes it an optimal solution.
• Python programming is straightforward to find out. A top quality Assurance engineer has got to specialise in software testing services, and learning new things shouldn’t become an obstacle. the straightforward syntax makes Python is the simplest programming language to find out from scratch. Besides, you'll find a bunch of useful materials online .
• It has readable code. It's convenient for scripting and supported by numerous tools.
• Python programming language is an (almost) universal language. Python may be a general-purpose language which will solve a huge array of tasks, it's utilized in web and desktop apps, data analytics, scripting, etc.
• It enhances team productivity. Where Python needs one line of code, Java uses ten lines. Python is concise, so it allows solving more tasks with fewer lines of code, leaving precious time to affect more complex tasks.
• The community is your backup. Massive code libraries assist you save time. You don’t need to reinvent the wheel but use ready code for import.
• Python script automation makes your life easier because it can automate your entire world – from the deployment of the test environment to continuous integration.

The Pros of Automation Using Python

We’ve mentioned a number of features that make Python in-demand and popular. Here are a couple of more words on AT in Python.
1.The Zen of Python, a set of guiding principles for writing on Python, is a perfect manual for test automation. It reminds you about the essential rules that make automated test scripts efficient. Tests should be simple and readable, obvious and relevant, complex but not complicated. Some would say this stuff are evident, but The Zen of Python may be a manifesto that won’t allow you to forget the fundamentals.
2.Pytest is one among the simplest available frameworks for automation available. It can handle any functional test, whether we’re talking about unit, integration, or end-to-end testing. Test cases are written simply as functions and may take parametrized inputs. Plugins extend pytest capabilities and permit you to hide code, run several tests simultaneously, and integrate with other frameworks, like Django and Flask.
3.A rich library of useful packages and ready-to-use ingredients for automation greatly facilitates testing in Python.
4.Python is object-oriented and functional. It allows choosing what suits your tasks better – functions or classes. Distributed functions don’t have side effects, and straightforward syntax makes them readable.
5.Command Line can drive the whole test automation workflow. Every test framework can launch a console for searching and running tests. Rich instruction support greatly simplifies test management. Moreover, automation with Python supports exploratory testing. you'll use Python calls to steer an app to some extent when manual testing is required.
6.Scalability makes Python equally great for beginners and experienced users. Scalability is achievable through syntax, superb structure, modularity, and a huge ecosystem of tools. it's also possible to integrate numerous side tools and processes.
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How to Learn Python - How does one learn everything else?

The strategy for Python doesn’t differ much. Find online courses, YouTube lectures and tutorials, and mobile apps to find out the fundamentals . If you grind to a halt at some point, find a mentor who can clarify the complicated topics. Getting conversant in the fundamentals usually takes 6 to eight weeks. Start with Python automation testing by writing simple programs from the very beginning. As your skills evolve, believe a tougher project and begin performing on it. Join online communities. Read earlier posts and ask questions. The advantage of online communities is a chance to urge a bit of recommendation supported real and sometimes recent experiences. Keep reading articles and tutorials as you learn and even after you become quite skilled.

Python Automation Frameworks

1.Python unittest (or PyUnit) may be a framework from the quality Python library and an excellent solution to start out with Python automation. It provides a basic set of tools that supports fixtures, test cases, test suites, and a test runner. Unittest is usually utilized in test-driven development. to get the complete potential, you'll also need nose2 with its system of plugins.
2.pytest – the simplest python testing framework for little projects. It supports compact test suites and offers quick bug fixing. It can run parallel tests and integrate with other test frameworks.
3.Robot – an open-source key-driven framework for acceptance testing that gives an upscale collection of tools and libraries.
4.Behave – a widely-used behaviour-driven framework. Written in semi-formal language, it's easy to read for QA team and non-technical specialists, opening opportunities for collaboration.
5.Jasmine – another BDD framework. it's easily integrated into Django projects, allows parallel execution of server-side and client-side test cases, and makes tests more resilient to changes.

AWS Cloud Security: The Best Practices

Companies today need to be agile and ready in the face of constantly evolving technology and changing consumer preferences. To achieve this goal, organizations are looking forward to switch to Amazon Web Services (AWS). Its services enables companies to rapidly deploy and scale technology that meets the growth (or shrinkage) demand without investing in expensive IT infrastructure. This is an efficient and cost-effective solution that creates it easier for businesses of all sizes to drive innovation. By now, though, most organizations are aware of the value delivered by AWS, yet many of them have a painfully low awareness regarding cloud security. ....

Given this, there is a wide range of AWS certification programs to help you acquire expertise on diverse AWS fundamentals, enclosed concepts and best practices related to cloud storage, load balancing, virtual private server (VPS), and AWS services.
These extensive training courses and certification tracks evaluate your professional abilities to design, configure, deploy, and administer AWS cloud services and applications proficiently.
Brillica Services is a leading training provider offering highly-demanded certification training courses equipped with practical implementation and hands-on learning.
The security model of AWS cloud computing service is predicated on the shared responsibility tenet. It implies that AWS is in charge of cloud infrastructure security, though the customer must strive to realize desired security levels within the cloud environment.
Brillica Services Best Project based Internship on Amazon Web Services Training course in Delhi and Dehradun, Uttarakhand .

Here are some best practices to enable you ways to travel about it:

Strategize: While the endeavours to achieve top-notch AWS cloud security are surely appreciable and advised, any attempt to achieve the required security levels without any planning will most likely end in disaster for the company. A precise cloud security strategy will not only keep the implementation process on track but also ensure desired levels of safety even as software is continually updated.
Cloud-native security solutions: Some companies could also be tempted to easily cope with conventional security solutions. Resist the urge in the least costs; instead, choose a cloud-native security solution that also offers consistent support, can safeguard AWS workloads, etc.
Embrace cloud security controls: Ensuring security is not just AWS’s responsibility; i.e., companies must also do their bit, including the implementation of various measures to make sure high levels of security. To that end, companies must unambiguously outline user roles, regularly organize and execute privilege audits to make sure users that don't need access any more don't have access, and leverage a robust password policy. Implementing other controls, including permission time-outs and multi-factor authentication, helps further alleviate risk.
Encryption is key: Most folks would think that encryption is now a typical procedure, but that's faraway from the reality , i.e., some companies often ignore this rather rudimentary requirement. Do not do that, please. Encryption is important for a variety of reasons, including the safety of sensitive data, regulatory compliance requirements, etc. AWS is very conducive to encryption, actually; all companies got to do is enable native encryption to safeguard all the info stored on the Amazon S3 service.
Prepare a response plan: in fact, the hope and goal are to make sure zero attacks; unfortunately, reality often tends to vary . Hence, the prudent thing to do in this regard is to hope for the best and prepare for the worst. In the context of AWS cloud security, this suggests the corporate must assume that an attack will indeed occur at some point and supported that, put together a plan of action for what to do when the attack occurs. Having a response plan to a breach ready to go allows companies to cut down the time it takes them to respond to such a situation.

There is not even a modicum of doubt that AWS may be a segment leader for lots of reasons. So, it's understandable that this behemoth within the cloud computing sector implements and enforces class-leading security measures to safeguard its virtual environments also as its many, many users. Unfortunately, these measures can still be undermined if users don't equally share within the responsibility of ensuring top-notch cloud security. If you've got been wondering the way to do this , we hope you discover the aforementioned best practices handy. And if you would like to require it up a couple of notches still, we highly recommend you search for a trusted name within the world of AWS software development services. Their expertise will lend your pursuit of security a spread of crucial benefits.

Give Wings to Your Career as a :-
Web Developer

Web development is the work involved in developing a Web site for the Internet (World Wide Web) or an intranet (a private network). Among Web professionals, "Web development" usually refers to the main non-design aspects of building Web sites: writing markup and coding. ....

How can I learn web development?

Learn the Basics of HTML, CSS, and Javascript.
Go through WordPress Tutorials.
Learn the Basics of UI and UX.
Learn SQL and PHP.
Learn the Basics of SEO.
Make Sure Your Site is Responsive.

What are 3 type of Web Developemnt ?

1. Front-end web development
2. Back-end web development
3. Full-stack web development.

Front-end Web Development

Front-end web Development, otherwise called customer side Development is the act of delivering HTML, CSS and JavaScript for a site or Web Application so a client can see and collaborate with them straightforwardly. Front-end deals with behavior and visuals that run in user browser
Front end programming advancement includes coding the client confronting parts of a site or programming program. Your obligations incorporate utilizing an assortment of devices or IDEs (coordinated advancement conditions) to compose or alter CSS (Cascading Style Sheets), HTML (Hypertext Markup Language), and Javascript code. Front-end Development alludes to that space of web advancement that spotlights on what the clients see on their end. . Web developer is a programmer who specializes in, or is specifically engaged in, the development of World Wide Web(www.)

Back-end Web Development

Backend Development is otherwise called server-side development. back-end deal with servers, It is all that the clients don’t see and contains in the background exercises that happen when playing out any activity on a site. It centers basically around information bases, backend rationale, APIs, and Servers. Web development can scope from grow a straightforward single static page of plain text to compound web applications, electronic businesses, and social network services.A back-end engineer is somebody who fabricates and keeps up with the innovation expected to control the segments which empower the client confronting side of the site to exist.A backend designer ought to likewise be capable in variant control frameworks like Git, GitHub, and GitLab. One should know about some well known Databases like MySQL, MongoDB, PostgreSQL, and so forth He/She ought to likewise be capable in social (SQL) and non-social information bases (NoSQL).

Full Stack Web Development

Full-stack Web development technology is the most comprehensive and complete in-house solution to develop engaging websites and applications for global enterprises. The Full Stack Web Development revolves around developing each layer of the software comprised of front-end, back-end, and the databases including all integral components such as UI and UX design, underlying platform and coding

Ethical AI : The Model Dilemma

Artificial Intelligence may be a tool a bit like the other - it's not inherently good or bad - it's the actors and their intents that matter here. AI is helping in healthcare and governance to improve people's lives. It is also getting used online for cheating, forgery, sowing discord, also as for advanced offensive weaponry. ....

Building AI with ethics may be a pertinent problem now quite ever as AI is being applied to more sectors.
Companies are not only using AI to recommend the next product to us, they are also using it in areas that are risk-sensitive. The extent to which machine learning is employed in safety-critical applications today has made the issues of ethical AI even bigger. .

We have not been ready to solve this dilemma from a person's perspective, how can we expect machines to know this?
“Growing complexity of systems and processes in business and governance, as well as the growing volume of our personal online and offline interactions - they all need AI solutions for better management. The ethics in AI, therefore, are hugely important”.
While the answer to ‘What is ethical’ varies for every industry, in basic it leads to the aspects of privacy, morality, transparency, security, solidarity. The ethics for AI include the purpose of AI’s deployment (healthcare or warfare), and the fairness in the AI’s decision-making.

But we need to make the Artificial Intelligence and Machine Learning models more ethical for people to trust it.
While Artificial Intelligence and Machine Learning are getting used to bridge the gap in many sectors, though we don’t trust these models enough to give them power to decide about life and death.
“Covid has been a raging issue for the last couple of years. There have been peripheral issues where ML was used, but not in many cases where it involved a risk of life -- despite the severity of the crisis. We don't yet trust AI and ML when it involves making decisions that affect a life”.
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As AI decisions influence and impact people’s lives at scale, it's crucial that organizations take a proactive approach to designing AI responsibly. Architecting and deploying AI models that are trustworthy, fair and explainable is the key. The conversation about ethics and responsible AI remains evolving and no-one has a definitive answer to how to move ahead. However, there have always been some best practices and things to keep in mind while designing and working with Artificial Intelligence and Machine Learning.
“Organizations got to adopt proven qualitative and quantitative techniques to assess potential risks and mitigate bias in AI models. Deploying the right set of tools and establishing practices to thoroughly and continuously investigate sources of bias and understand the trade-offs and impacts of fairness decisions is critical.”
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How to Become A Successful Java Developer?

Java is a commonly used language for web development, especially on the server-side. Java web applications are distributed applications that run on the internet. Web development with Java allows us to create dynamic web pages where users can interact with the interface ....

Build your carrer with AWS Cloud Computing

Build, Deploy, and Manage Websites, Apps or Processes On AWS' Secure, Reliable Network. Sign Up for a Free Account & Experience AWS' Secure, Reliable, Scalable Services. Easily Manage Clusters. Global Infrastructure. Secure Solutions. Highly Scalable. ....

Know more about Microsoft Azure Training

It is a cloud computing service created by Microsoft for building, testing, deploying, and managing applications and services through Microsoft-managed data centers. It provides software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS) and supports many different programming languages, tools, and frameworks, including both Microsoft-specific and third-party software and systems.....

Opportunities in Cyber Security

Cyber security is the practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks. It's also known as information technology security or electronic information security. ... Application security focuses on keeping software and devices free of threats.....

Give Wings to Your Career as a Tableau Developer

Tableau leverages the power to the enterprise management to see and understand data with utmost robustness and scalability and help in taking the right business decisions. For this reason, global organizations and the entire Business Intelligence industry hugely rely on Tableau developers. ....

Now, who are they, what roles and responsibilities do they execute, what skills you need to acquire to become one? How Tableau training can help you achieve your career goal? The article walks you through all this and much more.

Who is a Tableau Developer?

A Tableau Developer is the one who develops data visualization solutions to augment business processes. The role requires you to work with co-developers, create tableau dashboard reports, generate BI and visualization reports, take feedbacks and improve systems. The job is ideal for those who have strong business acumen, vast knowledge of mathematics and statistics fundamentals and exemplary data warehousing skills.

What are the responsibilities of a Tableau Developer?

Building Data Analytics Solutions: A Tableau Developer is entrusted with the core responsibility of devising technical solutions based on the enterprise needs. Translating business requirements and finding innovative solutions to it is the primary role of a proficient Tableau developer.
Testing: Querying databases, identifying issues and conducting tests to troubleshoot them forms an ongoing process through the entire software development project.
OLAP: OLAP stands for Online Analytical Processing. All Tableau developers need to preserve and secure data for which they create tools. OLAP is the technology behind the Business Intelligence apps and software that helps analytics and developers in complex computing calculations, data modelling, making data predictions and conducting trend analysis to facilitate business decisions.
System Enhancement: Constantly evaluating and improving existing business systems is the critical job role of a Tableau Developer, which is expected to be executed with the utmost competency. This requires seamless collaboration with the other teams on-board such that new processes can be streamlined and workflows can be managed well.
Creating Technical Documentation: All completed projects if documented well can help management to draw inferences and also refer to them to overcome future project challenges effectively. Tableau Developers key responsibilities include preparing technical documentation of all successfully executed projects.
Forecasting: Forecasting and storytelling are powerful features of Tableau that helps representing business data like no other BI tool. It empowers users to connect with data personally and deeply analyze it, make close forecasts with the embedded technique called exponential smoothening.

Which tools do Tableau Developers use?

BI technologies: Microsoft Power BI, Oracle BI
Data Analytics Tools: ETL and OLAP
SQL:SQL Server Integration Services, SQL Server Reporting Services

Why pursue a career as a Tableau Developer?

Natural language processing and machine learning-enabled data preparation are what Tableau is focused on. It is evolving with new technologies enabling futuristic approaches to view and analyze data. Soon it is going to launch hybrid data connectivity for the cloud.
These reasons would give you a clear understanding of the importance of pursuing a career as a Tableau Developer:
Tableau Market:Tableau is renowned to be the leader of all Business Intelligence tools and is crowned as the Best Data Analytics Tool by Gartner. They included Tableau in the Gartners magic quadrant for the 6th time in a row for its intuitive data analytics features and capabilities.
Tableau Job Opportunities: Along with soaring demand for Tableau experts there are exemplary rewards attached to it. Browsing top job portals such as Naukri and Indeed, you would numerous job openings for Tableau experts and developers. Tableau professionals are drawing the best salary packages in the IT industry with an average of $91,000 p.a.
Big Data and Tableau: Many global organizations depend on Hadoop for storing, wangling and analyzing data. Tableau seamlessly integrates with the Big Data Hadoop platform enabling users to easily identify valuable data in the expansive Hadoop datasets, without possessing knowledge of query languages and syntaxes.
This way Tableau expertise can help you comfortably fit into the Hadoop dependent environment.

Want to become a master in Tableau Dashboard and Data Visualization? Drop at Brillica Services Tableau Training
What skills and abilities you need to become a Tableau Developer?

A Tableau Developer should possess:
1. A Bachelors degree in Business, Computer Science, or similar field.
2. Experience in whole life cycle development of applications at the enterprise level.
3. Proficiency with SQL in large data sets.
4. Excellent analytical skills as they are needed to analyze the requirements of client or business.
5. Working knowledge of Tableau Software and project experience, such that they can solve any issue that occurs during the development stage.
6. Ability to create innovative solutions to problems within the business.
7. Self-motivation for finding solutions and improvements to systems during the phase of customer testing and prototyping.
8.Strong attention to details for spotting errors in data or coding.
9. Knowledge of Microstrategy and Data Architecture.
10. Effective written and oral communication skills.

How to acquire these skills and become a Tableau Developer?

Acquire a Certification in Tableau!
This would not only increase your chances of getting a career jump as a Tableau Developer but also open door to a plethora of career opportunities in Data Analytics. Getting trained and certified in Tableau helps you stand out from the crowd and validates your data analytics knowledge. Achieving Tableau certification and hands-on data analysis project knowledge requires attending a formal tableau training, which is the best way to hone your data analytics skills, learn about different tools and optimize them to the best of business interest.

"Tableau training at Brillica Services not only helps you master the key data analytics skill but also helps you understand statistics fundamentals, work with relational databases, prepare data and implement visual analytics in Tableau. Looking at the high demand for Data Analytics and Tableau professionals, extensive project-based tableau training can help you make yourself best fit for the role of Tableau Developer."

Top 10 Machine Learning Project Ideas for Beginners

Machine Learning is one of the in-demand technologies preferred by most engineering students who have a knack for programming and foresee their career in AI and Machine Learning domain. For any technology, no theoretical knowledge can replace hands-on practical knowledge and that is the reason why the best IT training companies are now embracing a project-based training approach. ....

Projects help you understand the practical implications of the learnt concepts and master it, which through books and training manual becomes quite a fantasy. Machine Learning projects familiarize you with the technology applications, real-time implementation challenges and help you explore the topics in deep and improve your applied Machine Learning Skills.
The article walks you through the most popular and engaging Machine Learning projects that can help you as beginners solidify your knowledge to the core and scale up to the next level of machine learning training and certification courses. Being the best investment that you make in carving your machine learning career, these machine learning projects will help you in learning all the practicalities that you need to succeed in your career and to make you employable in the industry.

Recommender Systems: Owing to the increasing demand from modern consumers for customized content, there is a strong need for machine learning students to discover how Netflix, Hotstar and Prime Video make movie and web series recommendations. One of the popular datasets available over the internet for beginners that can support in building a movie recommendation system is Movielens Dataset. This dataset includes more than 1,000,210 ratings for 4000 movies made by Movielens users, which can help you create a world-cloud visualization of movie titles to devise an effective movie recommendation system.
Stock Prices Predictor: This is another great machine learning project that can help data scientists and machine learning engineers to make their way to the finance field. Stock Prices Predictor system is software that analyzes a companys performance over a given period and predicts the future stock prices. Here you get to work on the granular stock prices data, volatile indices and also gain real-time experience of understanding macroeconomic and fundamental indicators that cause high fluctuations in stock prices. With shorter feedback cycles in financial markets, working on stock market data and validating the new price predictions become easy for the data scientists. Based on fundamental indicators from the companys quarterly report and analyzing 6-month price movements, you may start with a simple machine learning program and predict the new stock prices.
Sentiment Analyzer: Social media data generated in huge volumes through diverse platforms such as Twitter, YouTube, Facebook etc. is of extreme importance in marketing and business branding. Mining this social media data can help in understanding public sentiments, trends and opinions. A sentiment analyser system considers different content pieces picked up from emails, tweet, social media posts through machine learning algorithms and predict further. For beginners, Twitter data is the best to start with and practice sentiment analysis machine learning use cases. The project becomes engaging with tweet contents comprising metadata, hashtags, location, users, retweets and more to help draw insightful analysis. Working with the twitter dataset will help you understand the challenges associated with social media data mining and also learn about classifiers in depth. The foremost problem that you can start working on as a beginner is to build a model to classify tweets as positive or negative.

To access the codes and experience the challenges, drop atBrillica Services for extensive project-based machine learning training.

Neural Network That Reads Handwriting: Neural networks and deep learning are two emerging branches of modern artificial intelligence, which have led to major progress in image recognition, automatic text generation, and even in self-driving cars. To learn this, you need to begin with a fairly manageable dataset. The MNIST Handwritten Digit Classification Challenge is the perfect entry point. Image data is generally harder to work with than flat relational data, for this reason, The MNIST data is quite beginner-friendly. It will be challenging but not undoable as it doesn't need high computational power. Enrol now for the most desirable project-based machine learning training to master solving image recognition problems
Movie Success Rate Prediction System: The success rate of a movie is largely dependent on peoples perception and opinions, through word-of-mouth. In todays digital world, word-of-mouth is prevalent in the form of reviews found online. The opening day and the first few weeks following a movies release is crucial, and hence production houses place a lot of importance on moviegoers opinions and develop trailers and publicity strategies to sway public opinion. Taking this into account, the project concentrates on building a review system for predicting the success rate of a movie.
Credit Card Fraud Detection System: Companies that depend on credit card transactions need to find anomalies in the system, for which this credit card fraud detection model can be helpful. This project aims to use the transaction and their labels as fraud or non-fraud to detect if new transactions made from the customer are fraud or not.
Uber Data Analysis Project: The Uber Data Analysis project is an excellent way to learn and perform data visualization. The Uber dataset contains data about 4.5 millions of uber pickups, and the project requires you to represent this rides data in a way to help make further improvements in the business.
Fake News Detection Project: Distinguishing the fake news from the real ones is the ultimate goal of this Fake news detection project that can help you solidify supervised learning concepts and implement this model.
Housing Prices Prediction Project: House Prices Dataset consists of housing prices for different locations of a particular region. The dataset encompasses the 14 other attributes including information about house/building age, crime rate, people age etc. The objective of this machine learning project is to predict the selling price of a new home by applying basic machine learning concepts on the housing prices data. The project is appropriate for machine learning beginners to gain hands-on practice on regression concepts.
Wine Quality Test Project: It is known to all that older the wine, the better is the taste. However, not just age but wine quality testing and certification take in many more factors dependent on physiochemical tests to check fixed and volatile acidity, density, PH levels and more. The primary objective of this Wine Quality test project is to build a machine learning model to predict the quality of wines by exploring their various chemical properties.

"The machine learning industry will continue to grow for years to come. While some people see the so-called rise of the robots as the end of the personal touch in business, the reality is quite the opposite. There are so many great machine learning projects that help companies offer a better service, effectively humanizing brands by making them more in tune with the interests of their target audience. Its not easy to develop your first machine learning project. By learning from us, you can create something great. Brillica Services Machine Learning Engineering Training and Certification courses are the first of its kind that is focused on project-based learning and come with a job assistance guarantee."

Top Data Science Tools Everyone Should Know

Data Science is amongst the most popular fields of 21st Century and nothing to wonder if I tell you that it is the key methodology behind revolutionary technologies like Artificial Intelligence and Machine Learning. With voluminous data at the disposal of global organizations, ....

Data Scientists need to deploy and ensure effective use of numerous data science tools to help organizations manage and analyze large structured and unstructured data sets for lending support in making strategic business decisions.
The article brings you the most popular data science tools that Data Scientists and business analysts use in their work life. First of all, you need to understand that Data Science tools can be categorized into those used by:

Non-Programmers

Programmers

Perhaps, this sighs relief to those even who do not have in-depth knowledge of programming languages. This means that Data Science is a technology that can be learnt by those who do not have an upper hand in programming capabilities.
The Data Science tools that can be used by non-programmers include:

Rapid Miner
Data Robot
Trifacta
IBM Watson Studio
Amazon Lex and more.

On the flip side, programmers have access to an array of Data Science tools which help them create predictive models, visualize and analyze diverse data patterns in the favour of businesses. Top Data Science tools used by Data Science professionals are:

Tableau:

Tableau is a robust Data Visualization software packed with compelling graphics making it the most interactive Data Science tool of the era. The most important aspect of Tableau is its ability to integrate data from diverse resources, OLAP (Online Analytical Processing) cubes, geographical data visualization and much more.

TensorFlow:

TensorFlow has become a standard tool for Machine Learning and is extensively used for advanced machine learning algorithms like Deep Learning. Known for high performance and computational capabilities, TensorFlow is an open-source and ever-evolving toolkit used by programmers. It runs on both CPUs and GPUs and has recently emerged on more powerful TPU platforms, giving an unparalleled edge in terms of the processing power of advanced machine learning algorithms.

SAS:

SAS- a popular data science tool designed for statistical operations, is used by major global enterprises to analyze data and draw insights. SAS uses base SAS programming language for performing statistical modelling. Offering expert statistical capabilities of creating a predictive and analytical model and organize data, SAS is expensive and is trusted by large industries.

Python:

Both, a popular and a powerful programming language, Python is the perfect Data Science programming tool for developing custom algorithms used by Data Scientists in analyzing huge raw data sets efficiently. As Python is used in Data Science and back-end development, it provides a solid platform for developing machine learning models too, leveraging utmost security of the implemented tools.
For Python and Machine Learning Certification Training, drop by Brillica Services in Dehradun.

EXCEL:

Developed by Microsoft, Excel is a popular Data Science tool used by data analysts, business intelligence experts as it features strong inbuilt capabilities of spreadsheet calculations, data processing, visualizations, complex sorting and lookup functions. Excel comes with various formulae, tables, filters, slicers, etc. You can create custom functions and complex formulas in Excel to efficiently analyze the given data. Embedded with the power of data visualization and graphs, Excel is by far an ideal choice of all Data Scientists. Seamless integration with SQL makes Excel easy to use and analyze data on the go. A lot of Data Scientists use Excel for data cleaning as it provides an interactable GUI environment to pre-process information easily.

R-Language:

Similar to Python but more specifically built for Data Science, R is yet another preferred programming language for Data Scientists. An authentic poll revealed that 48.5% of respondents voted it to be one of the leading data science tools. With machine learning, statistics and prominent data analytics features, data science professionals preferably use it in the enterprise environment. Some of the statistics use of R include calculating mean, median, quartiles, build hypothesis, apply data tests and explore it to the core to help management base their business decisions on it.
Seeking R language certification in Dehradun? We have Brillica Services for you!

Hadoop and Apache Spark:

Specifically designed to handle and process data in batches and execute stream processing, Apache Spark is an all-powerful analytics engine that facilitates Data Scientists associated with global organizations.
It comes with many APIs that facilitate Data Scientists to make repeated access to data for Machine Learning, Storage in SQL, etc. It is an improvement over Hadoop and can perform 100 times faster than MapReduce. Spark has many Machine Learning APIs that can help Data Scientists to make impactful predictions with the given data.

Conclusion

We recapitulate that data scientists require a vast array of tools to draw inferences from unstructured data sets and provide support in making the right business decisions. The mentioned popular data science tools are widely being optimized for analyzing data, creating aesthetic and interactive visualizations and creating powerful predictive models using machine learning algorithms. Alongside easing complex data science functions, these data analytics tools help in implementing data science functionalities without having to write their code from scratch.
If you wish to enrol for a complete course on Data Science, Artificial Intelligence and Machine Learning, Brillica services offers a uniquely curated Data Science Masters Program and Machine Learning/AI Certification course to help you gain proficient data science skills, in-depth knowledge on machine learning techniques like Supervised Learning, Unsupervised Learning, and Natural Language Processing and much more. It includes training on the latest advancements and technical approaches in the field of Data Science, Data Analytics, Artificial Intelligence & Machine Learning and much more.

Explore the future of Data Science with Brillica Services!

How Brillica Services Best Summer Training in Data Science Can Make Your Career Bright

On the verge of the end of last year of engineering, career-building tension is high on the minds of many. For a bright career, you need to have and showcase something extra, now that extra could be sound knowledge and hands-on experience over an in-demand technology.How about a summer training in Data Science? ....

What if I say that in just 6 weeks you can acquire skills that have great job demand? What if in 6 weeks this summer you can make yourself employable?

Yes, you read it right 6-week project-based summer training in Data Science is capable of giving that much strength to your resume that you can get a career-kick start immediately and plunge your career to new heights by carving your niche in the field of Data Science.

Future of Data Science and its Learning Relevance

Data Science careers are buzzworthy these days and the reasons that contribute to making it the career of the future include:

Staggering Data Growth:

It might be shocking to know that people generate data a tremendous amount of data daily and that too without being aware of it. According to recent research on data growth, approximately 5 billion consumers interact with data daily and this number is expected to rise to 6 billion by 2025, which constitutes around three-quarters of the worlds population. Adding to this, total data amounted to 33 zettabytes in 2018 and the projections reveal it to rise to 133 zettabytes by 2025. With so much of data production, there is an urgent need for data science professionals to be at the forefront and help global organizations manage them effectively.

Large Companies Struggling With Data Management:

Data is like blood for all businesses; therefore data inflow cannot and shouldn't be stopped or be barred at any cost. But huge volumes do impose challenges to the companies in managing it effectively. According to Data Security Confidence Index, 65% of businesses find it difficult to analyze and categorize the data they have on their dashboard. Also, 89% of them know that if analyzed critically, they can have a competitive advantage. For this, large companies are ready to invest a handsome amount in the form of salaries to data managers, Data Analysts, Data Engineers and Data Scientists, who have in-depth knowledge of the data analytics tools and hands-on project-based training in Data Science.

Introduction of GDPR Norms:

The General Data Protection Regulation (GDPR) which was introduced in 2018 took effect for countries in the European Union. Its expected from California also to come up with a similar data regulation policy to ensure data privacy and confer data protection rights to the consumers. This GDPR has increased the demand for Data Science professionals steeply as companies need someone who can abide by the laid regulations and also help them with competent data analysis to ensure business profits. With rising cases of data thefts and vulnerabilities across the globe, the demand for Data Analysts, Data Scientists and data security experts is on the highest.

Evolving Technology:

Careers without growth possibilities become stagnant, usually indicating that jobs within those respective fields must drastically evolve to remain germane. Data science seems to have plentiful opportunities to progress over the next decade or so. Since it shows no signs of slowing down, it is good news for all the young data science aspirants wanting to enter the field.

Career Advancement Opportunities:

LinkedIn survey declared data scientist as its most promising career of 2019. One of the reasons it got the top spot was that the average salary for people in the role is $130,000. LinkedIn study also looked at the likelihood that people could get promotions as data scientists and gave a career advancement score of nine out of 10. Data Science training and hands-on experience of working over live projects can be your key to unlock the career opportunities to land into the roles of:

Modelling Analyst
Product Data Analyst
Business Intelligence expert
Machine Learning Engineer
Hybrid Data Engineer
Data Visualization Expert
Data Science platform and tool developer and much more

Data Science Summer Training @ Brillica Services

As the data volumes are on the steep rise, there is an urgent lookout for methods to get valuable insights on it. As a result, there is a desperate need for professionals with proficient data science skills. Data Science Training is a way to see your dreams come true. All leading industries at global locations are starving for data science professionals, but surprisingly the field registers a wide skills gap. Take note of these facts:
A LinkedIn report claims that there are 151,000job postings for data scientists being felt in big tech hubs like San Francisco, New York City, and Los Angeles.
According to a Harvard Business Review study 40% of companies claim they are unable to hire or retain data talent due to a lack of supply.
Looking at the ocean of opportunities in Data Science with numerous top organizations like Google, Amazon, Deloitte and more, ready to pay high packages have set the domain on fire making it the hottest tech domains to learn. Data Science training is considered essential for all graduates, professionals and fresher folks who are looking for a career as a Data Scientist.
Brillica Services offers an array of summer training courses delivered through industry experts who are focused at imparting the much demanded Data Science analytical skills through live industry projects, making you readily employable at global organizations.

Data Science Summer Training Benefits @ Brillica Services

6 weeks of intensive Data Science summer training program in Dehradun at Brillica Services premises offers you the following advantages:
Personal Training assistance from certified mentors

Chance to work on live industry-projects

Access to expertly-curated curriculum

Opportunity to get trained from top academicians and industrialists

Great opportunity to gain proficient data science skills from your fellow peers

Boost your profile strength thereby providing a higher level of opportunities

Chance to get hired as interns at esteemed organizations

Recognized certificate of completion and much more

"Invest your time and efforts this summer in learning Data Science technologies at Brillica Services and secure your future!!"

PMP FAQs: All That You Must Know About How to Prepare for the New PMP Exam

Staying ahead of the competition and surviving in the global economy form the core motives, turning the organizations to project management, with a tenet to attain consistent growth in business results.....

The global organizations believe that a disciplined approach to the project, portfolio and program management can deliver the expected business value at every stage, leading to investing significantly on hiring project management experts and leverage greater efficiency, enhanced stakeholder faith and satisfaction. PMP certification is the key to it that can help you unlock an array of project management career opportunities and acquiring critical management skills. So, What is PMP certification all about, its eligibility criteria, exam format and how to prepare for PMP Certification exam and many other queries stand answered in this blog.

What is PMP ?

PMI (Project Management Institute) offers the globally renowned certification, known as PMP (Project management Professional), that is acclaimed as a standard measure of the project management competencies. Acquiring PMP certification credentials are prestigious for project managers to validate the cutting-edge skills to plan, organize, implement, control all project phases and efficiently managing resources, stakeholders, time and efforts driving projects to success.

Who can take PMP certification?

Project Management Professional certification can be aimed by experienced project managers who:

Shoulder the responsibility of executing projects under supervision and are familiar with all aspects of the project lifecycle

Lead the project teams and direct them to adhere to project deadlines and simultaneously adhere to a defined budget, schedule and resources

Demonstrate pertinent knowledge of applying the suitable methodology of executing clearly defined projects.

What is the pre-requisite to take PMP certification Exam?

Taking the PMP certification exam requires you to qualify one of the listed criteria completely:

A high school diploma, an associate degree, or its equivalent with a minimum of 5 years of project management experience constituting 7,500 hours in leading project tasks and 35 hours of PMP training classes.

A 4-year educational degree with at least 3 years of experience in project management founding 4,500 hours of leading projects and 35 hours of formal PMP certification training.

What is the format of the PMP Exam?

The current PMP exam format is based on 5 performance domains and contains 200 multiple choice questions that need to be answered in 4 hours.
The exam questions are segregated into 5 process groups based on PMBOK Guide, to test your practical approach of handling complex project situations:

Initiation (13%)

Planning (24%)

Executing (30%)

Monitoring and Controlling (25%)

Closing (8%)

But according to the PMI announcement regarding the recent PMP certification changes, from 1st July 2020, the PMP exam would be based on 3 domains including:

People (42%)
Process (50%)
Business Environment (8%)

Is the PMBOK Guide also changing?

No, PMP certification and training programs would continue to follow the PMP bible PMBOK 6th edition in the same way as the seventh edition is not expected to be out before 2023. The change is to be brought into the ways how to prepare for PMP exam considering the new format and the tested modules.

What is the passing criteria for PMP certification?

The PMP certification measures and scores your understanding as:

Proficient

Moderately Proficient

Below Proficient

Based on the achieved proficiency levels in all domains an overall performance report is generated that defines your result. There are no specific criteria related to a minimum or maximum domains you need to attain the proficient levels to pass the PMP exam.

How many PMP Exam retakes can be taken?

You can retake the PMP exam thrice in one year. Based on the score report, generated after submitting the exam, you can analyze your proficiency level for all the performance domains and prepare accordingly before retaking the exam to save on the cost and efforts.

How to prepare for PMP?

Preparing for PMP certification exam requires you to have profound understanding and approach to implementing the project management knowledge areas, processes in different project stages, that can be achieved by enrolling into PMI authorized training centre offering extensive PMP training and certification courses. The PMBOK sixth edition based PMP training classes, delivered by industry experts can help you prepare and pass the tough exam with striking scores.The project management professional training classes are made available to you in blended learning modes that can be customized to meet your specific learning needs.

Should you take the PMP Exam before or after the 2020 Update?

Before July 2020 is always advisable for all those who are already taking PMP training classes and preparing for the PMP exam from long, because, after July, it is certainly going to be tougher.
Usually, it takes 8 -10 weeks to get trained and self-study the learnt PMP fundamentals. So, if you are reading this, you still have to take the chance and achieve the most prestigious PMP credentials now. Brillica Services can help you get closer to your career goal through extensive PMP training and certification course as we understand that your opportunity window is getting smaller day by day.

Project-Based Summer Training in Python & Machine Learning in Dehradun, Uttarakhand

Are you an engineering graduate or pursuing it and aiming to enter the tough job-market full of neck to neck competition with your academic knowledge?....

Well, it is certainly not enough, because we have thousands of engineering students parallel to you with the same knowledge and competencies. However, one thing that can set you apart is only hands-on experience! Today all organizations prefer hiring those students who are technically sound, creative and analytical and who can start performing from day one. They do not want to invest their resources in training you before putting you to work. Therefore, A quality solution to this is undertaking project-based summer training to validate your practical knowledge and technical expertise over a specific technology.

Why take Project-Based Summer Training in Python and Machine Learning

Importance of Python and Machine Learning

IT industry in India has shown phenomenal growth in the last decade. With innovative technologies evolving every day, the Indian IT industry is set to become the fastest-growing market globally in the next ten years. Being an engineering student, you must not be confined to only theoretical knowledge, but also have an idea about the acute details of latest technologies, its applications and scope in the future. Every engineering student now is capable enough to understand the importance of building hands-on projects. More projects in your profile, more capable you are in the eyes of the recruiter. Your projects speak louder than your college marks and certainly give you an upper hand during the process of placements.
Of the emerging technologies, Python and Machine Learning have seen unprecedented growth in popularity, recognition, career and scope. For this reason, most of the engineering students are investing their crucial summer training break into project-based summer training in Python and Machine Learning.

Amazing Python and Machine Learning growth facts

According to IBM, Python is the most popular language for machine learning

The market size of Machine Learning is expected to grow from $1.41 Billion in 2017 to $ 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1%

Knowing these, who would miss on the opportunity to make a career into the booming domain of Python and Machine Learning?

Whats so unique about Project-based summer training in Python and machine learning in Dehradun?

Over the years the trends have revealed that Dehradun has become a most desirable place to stay and learn for young technocrats as the place is blessed with the scenic beauty of nature and pleasant climate and is surrounded by esteemed engineering colleges. Preparing you for the growing industry with a wide array of course choices on emerging technologies, Brillica Services is one of the pioneering technology training institutes that believe in learning through project implementations.
Most engineering students having a knack for programming and aspiration to carve careers in Artificial Intelligence domain choose project-based summer training in Python and Machine Learning at Brillica Services in Dehradun.

It is a 6-week course where the curriculum is concentrated on instilling in-depth knowledge and understanding of practical implications of the learnt concepts through live industry projects. Such extensive and expertly curated course helps you become job-ready and upfront the corporate challenges fearlessly.

Exhaustive project-based summer training at Brillica Services acclaims to make readily employable with the industry-relevant Python and machine learning skills by developing a broad industry outlook. Constant inclusion of beginner to advanced level python and machine learning projects in the summer training here in Dehradun helps you step ahead in your learning and career journey progressively.
Besides the above factors, other reasons to seriously pursue the Python and Machine Learning summer training program is to:

Gain in-depth technical knowledge of the Python language, functions libraries and understand how it applies to the machine learning algorithms.

Enhance technical skills in a real-time environment.

Take a deep dive into the specialized machine learning projects, algorithms and chase your area of interest by gaining specialization gradually.

Develop skills to work in a team.

Improve awareness of the industrial environment and work culture of the Python and machine learning industry.

Develop an analytical approach to build real-time machine learning projects using Python codes.

Interact with industry experts; seek constant mentoring and guidance to resolve queries with practical exposure.

6-week project-based summer training Certificate from Brillica Services adds strength to your profile and resume as the courses are recognized.

Open doors to job opportunities in reputed tech organizations exhibiting your skills and knowledge.

Projects during summer training help in validating your core Python and machine learning competencies making it easier for the future employers to judge your capabilities and skills.

Closing Thoughts

If you have made your mind and are really serious about your career then you must not waste your precious summer vacations this year in bluffing your seniors by purchasing ready-made projects, instead take up the 6-week summer training in Python and machine learning in Dehradun at Brillica Services, that makes it non-tedious yet engaging for you. Our certified industry experts specialize in instilling in you the most sought-after python and machine learning through live industry-projects that help you get acquainted with the industry scenarios, challenges and ways to resolve it analytically.

Machine learning with python training course

What is Machine Learning with Python?

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of Computer Programs that can change when exposed to new data.....

What Is Python Used For?

Python has become one of the most popular programming languages in the world in recent years. Python used in everything from machine learning to building websites and software testing. Python can be used by developers and non-developers alike. Brillica Services provides the best Python programming training in Dehradun, Uttarakhand, Delhi.....

Python programming language is one of the best programming languages used nearly in all AI and machine learning operations. Python is a highly sought-after skill by software professionals, app developers and beginner programmers.

What is Python?

Python programming is the most popular and powerful programming language used nearly in all AI and machine learning operations. Python is a highly sought-after skill by software professionals, app developers and beginner programmers. This powerful object-oriented Python programming language is featured with high extensibility, large standard library, portability and embed-ability making it popular in domains of data analysis and visualization, AI and machine learning, application back-end framing, desktop app development and much more.

Python is a well-liked programming language. It can create web applications, connect to database systems, also read and modify files, handle big data and perform complex mathematics, rapid prototyping or production-ready software development. Alongside software to create workflow. It works on dissimilar platforms like-windows, Mac, Linux, raspberry pi, etc it has straight forward syntax similar to English language and also permits developers to write programs with other programming languages or it treated in procedural way, or a functional way. The syntax contrasts with other programming languages and is designed for readability or use new lines to complete a command, as against other programming languages which frequently use semicolons or parentheses. It runs on an interpreter system (code can be executed as soon as it is written), this means prototyping can be very quick.

In python we learn to code like an actual programmer, learn how to leverage built-in modules and functions to efficiently optimize your code as skills developers, and an understanding of software engineering concepts, including modularity. Python is an interpreted object-oriented, high-level programming language. Python is an open source programming language. It interpreted object-oriented, high-level programming language with dynamic semantics. Widely used for web development, system scripting, software development, system scripting, and software development. Python supports easy syntax which helps to write programs in very few lines. A programming language is a tool to calculate and conduct your discovery. It is a very important task in data science to deal with data.

Why Is Python So Popular?

Python is popular for a number of reasons. Here’s are some points:

1) Easy to Learn and Use
2) Mature and Supportive Python Community
3) Support from Renowned Corporate Sponsors
4) Hundreds of Python Libraries and Frameworks
5) Versatility, Efficiency, Reliability, and Speed
6) Big data, Machine Learning and Cloud Computing
7) First-choice Language
8) The Flexibility of Python Language
9) Use of python in academics
10) Automation

The Importance of Data Science in Modern Business

How important is Data science in your modern business? For many companies, the answer is very. Data science offers an opportunity to take in large amounts of data from different sources, clean and organize it, extract meaningful insights, and put those insights to work to drive business decisions forward. The ability to conduct data science properly can make the difference between success and failure, particularly in competitive industries where every decision counts. We will tell you about the Importance of Data science in modern world and how it is useful for business.....

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