Certificate in Big Data Analytics for Business & Management

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Program Description and Objectives

The program covers all essential components that today constitute a Modern Data Science Course. It covers in depth Machine Learning, it has a detailed coverage on Deep Learning and NLP; it covers Hadoop, Spark and streaming analytics using Kafka and above all it also covers NoSQL databases. The program has two special emphasis: One on Healthcare Analytics and the other on Reinforcement Learning. One of the biggest consumers of Big Data technology is healthcare sector. Reinforcement learning is finding huge applications in Self-driving cars, Industry automation, Trading and Finance, Natural Language Processing, Healthcare and Recommendation Engines.

No other course on Big Data Technology in the country would cover these two modules. We also bring in Cybersecurity. Cybersecurity is an essential requirements of ant IT system.

Our pedagogy is very practical. First, we stress concepts and avoid mathematics. Second, we lay-emphasis on project work from Industry. Our objectives are very clear: As soon as a student has finished the course, he should have sufficient experience in execution of ML & AI projects.

  • Covers Machine Learning, Deep Learning and Big Data technology
  • Covers streaming analytics, big-data storage systems (Hadoop and nosql)
  • Has a module for Healthcare analytics and Reinforcement Learning
  • We have a module for Cybersecurity
  • All modules are heavily practical oriented. Students are encouraged to perform a good number of projects
  • Every student gets personal attention, even though teaching is online.
  • Our e-learning platform is extremely rich in resources and students continue to access even after the course has finished.

Who should attend

Data being ubiquitous, the program cuts-across job or academic profiles. The techniques taught are generic in nature. Non coders are welcome. These will be valuable to anyone who wishes to interpret data to advance his/her knowledge and insights of environment. Specifically, the course will be useful to:

  • Students/Research Scholars: 3rd & 4th year students currently enrolled in Engineering / MBBS or 2nd year students of PGDM/ MBA or any graduate or post-graduate program who have had an introductory course in Mathematics & statistics. These students can look forward to better placement opportunities with added skill set.
  • Executives: Ambitious Executives from IT (from Private/Public sectors) with 0-8 year of experience looking forward to sharpening their skills in making sense of data in order to innovate and add more value to their organization and to society.
  • Data Scientists/ Developers: Techniques taught to them will have applications in a broad array of disciplines.


Program Duration: 7 Months Approx

Course Schedule

Two Sessions of 3 hours per week on Sat-Sun

Class Timing

Saturday - 10:30 AM to 01:30 PM

Sunday - 10:30 AM to 01:30 PM

Assessments & Evaluation Methodology

3 Section level MCQ based assessments. 1 Capstone project implementation.

Program Delivery

The sessions will be delivered on Tech Mahindra interactive learning platform.

  • Immersive Learning Using Case analysis, Assignments, and Projects.
  • Online Live interactive classes supplemented by Assignments etc and group work.
  • Cases and Handouts are given before the class to be solved and discussed in weekend live classes.
  • Assignment and Group Projects for practical application of theoretical concepts.

Total Fees

Course Fee :

Rs. 75,000/- + GST (INR 5,000/- discount in case of lumpsum payment.)

Other Fee :

Rs. 5,000/- + GST : Books and Material(Mandatory Fees)

Collection of Fee:

Program Fees (Part A)
Installment Schedule Registration Fees Admission Fees 1st Installment
Installment Amount 10,000/- + GST 35,000/- + GST 30,000/- + GST
Installment Date At the time of Enrolment TBD TBD

Program Content

  • Data Mining and AI (133 Hours)
    • Machine Learning algorithms (35 Hours)
    • Deep Learning, AI and NLP (51 Hours)
    • Hadoop, Spark and Kafka Eco Systems, Data stream processing and analysis (35 Hours)
    • NoSQL and Graph Databases (12 Hours)
  • Capstone is intended to be a guided walk through a day in life of a typical data scientist. Techniques and technologies learned are brought together and applied on a real life project. (20 Hours)
  • Healthcare Analytics Case Studies (15 Hours)
  • Cyber Security (15 Hours)
  • Reinforcement Learning (10 Hours)
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Assessments: Based on Performance in Exercises & Projects

Tech Mahindra Ltd.

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