Data Science Training

Besides providing fundamentals of Data Science, Mindmajix training assists you in completing the valuable certifications, taking up real-time projects, and helps you in placements in the top companies of the industry. There are various options available based upon your availability to take up this training -- Self-paced training, Online instructor-led training, and corporate training. 

Furthermore, Mindmajix offers you Data Science training with the Python language, which is a user-friendly English-like language and easy to learn. Python is most commonly used these days because of its simple syntax, robust library, portability, and web usability.

Mindmajix also encourages you for this training by providing you 24/7 support, allows you to pay in two instalments, and most importantly, it can be designed based upon your specific needs.

The demand for Data Scientists is increasing every day. Huge data is available in the market, but the challenge lies in analyzing this database that shows the road map for business to grow. These days, companies are in tough competition to leverage big data analytics and data science to get the nerves of users first, to benefit from the first mover’s advantage.

• According to a survey conducted by IBM, up to 2,720,000 data scientists job openings will be there in 2020.

• Every organization has realized that they need data scientists to gain maximum benefit from the available data.

• Almost all the sectors including cyber-security, healthcare, defence, education, IT need data scientists.

Getting certified in Data Science is beneficial for the following job roles:

• Big Data, Analyst and Business Intelligence Professionals
• Machine Learning Professionals
• Predictive Analytics and Information Architects
• Big Data Statisticians
• Individuals seeking a Data Science career

Your interest and willingness is the only thing you need to have for attending this training. Even if you can’t pay the whole amount at one time, we encourage you to pay in two instalments but don’t stop you from the enrollment. Mindmajix is completely focused on your learning, gaining knowledge, and getting a good job.

After completing this training, the learners will be in a position to master the following areas:

• Roles and responsibilities of a Data Scientist
• Machine Learning algorithms
• Integrating R with the Hadoop ecosystem
• Linear and logistic regression
• Clustering, analysis segmentation, and prediction
• Deploying recommender systems
• Data interpretation, plotting techniques, and sampling methods

Based upon the responses received by Payscale.com, the average salary of an entry-level data scientist can be 508,682/-. IT professionals with 5-9 years of experience can expect an average salary of  610,811/- whereas, with 10-19 years of experience, a Data scientist can expect 1,724,618/-

In the US, a Data Scientist can earn $ 113,309 on an average.

This is a prestigious job, the name Data Scientist itself has a great weightage in itself. When compared to other jobs on the same level of experience and for the similar kind of educational background, you earn more comparatively. It’s just a matter of your interest! If you are interested in working smartly and creatively, and earn more, this role is waiting for you.

The first milestone for a Data Scientist aspirant is to learn programming languages such as Python, R and get hands-on analytical tools such as SAS. The next stage could be getting knowledge of big data analytics and statistical tools, for example, Hadoop, Spark. Yet another milestone could be understanding of visualization, charts, maps, and reports to analyze the large chunk of data.

You as a Data Scientist have enough potential to give the direction to your business -- the shortest path to succeed. You perform data analysis, data mining, statistical analysis using available tools to predict the solutions for better business performance.

Almost all companies have started creating positions for Data Scientists including  Microsoft, Google, Amazon, Accenture, IBM, and Capgemini.