Certificate in Big Data Analytics for Business & Management - Batch04

Program Description and Objectives

Applications of Big Data transcend all disciplines. Use of predictive analytics pervades diverse disciplines such as oil and gas, marketing and sales, sports, molecular biology, drug-designing, waste management, finance and the list is indeed very long.

How different Sectors/Industry use Big Data

  • Smart cities, are the melting pot where a variety of big data technologies mesh with one another to transform a city into a semi-intelligent being.
  • In Marketing and Sales, Big Data is fast emerging as a potent tool to gain deeper insights into Customer behavior and thereby act as a strong driver in spurring innovation.
  • In manufacturing, operations managers are employing advanced analytics on historical process/data to identify patterns and relationships among discrete process-steps and inputs, and then optimize the factors that prove to have the greatest effect on yield.

Broadly the course has three parts: Analytics, Hadoop-Eco System, Deep-Learning & AI. At the end of this course, given a large dataset from any domain,a participant will learn to:

  1. Clean, transform and visualize a dataset to gain deeper insights and make it ready for analysis
  2. Select a subset of appropriate machine learning algorithms that could be applied to get the desired predictive results
  3. Gain sufficient proficiency in tools necessary to implement ML algorithms
  4. Use of relevant tools and techniques to get a reasonable predictive accuracy
  5. Apply the knowledge of Deep Learning & Artificial Intelligence to a wide array of disciplines such as health, process control, navigation & others.
  6. Install, Setup, Configure and Experiment with a complete Hadoop and Kafka ecosystem, and be sufficiently familiar with the variety of NoSQL data bases and decide for him/herself which one to use, when and how

This course is project oriented: All tools, data and platforms including Hadoop-ecosystem and Kafka(Spark)-streaming technologies necessary for learningdata-analytics are provided to the participants in advance. There is a heavy emphasis on open-source technologies universally used almost throughout theindustry. Each participant, at the beginning of the course, receives Virtual Machines (VMs) fully equipped with all the software platforms, tools,packages and data to work on. We make the whole process very simple and stress-free. Details of Virtual Machines can be seen here

Complete Program is project based. We have experience with several Industrial projects. Students execute these and other projects while implementing techniques learnt and as part of weekly exercises.

Who should attend

Specifically, the course will be useful to:

  • Executives: Ambitious Executives (from Private/Public sectors) 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.
  • Academicians: Lecturers and Professors for extending the horizon of their knowledge through deepening their research skills.
  • Data Scientists/ Developers: Techniques taught to them will have applications in a broad array of disciplines.

Pedagogy

We strongly believe that a course in data analytics can only be practice-based rather than theory based. The teaching pedagogy will be like this: First, the technique/algorithm is conceptually explained without getting into mathematics and then a project is undertaken to implement the technique. Datasets for implementation are made available in advance and so also a copy of code we need to execute. The code is numbered and copiously commented upon so that long after the lecture has finished, students can go back through the code/comments and refresh their knowledge. During the lecture, we execute this code, line-by-line and explain the steps. At his/her end, the student also execute the same code and may seek clarification. Consequently, results are available at our end as also on Students’ Laptop.

Program Duration: 6 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

Based on Performance in Exercises & Projects

Program Delivery

The sessions will be delivered on TechMahindra Growth Factories interactive learning platform.

Course Material

Course material will be shared either through cloud or in hard copy with all the participants at the appropriate time.

Total Fees

Course Fees are payable by Student directly to Tech Mahindra Growth Factories Limited

Course Fee :

Rs. 60,000/- + GST

Rs. 50,000/- + GST (One time payment)

Other Fee :

Rs. 5,500/- + GST : Book and Material(Mandatory Fees)

Collection of Fee:

Program Fees (Part A)
Installment Schedule Registration Fees Admission Fees 1st Installment
Installment Amount 10,000/- + GST 25,000/- + GST 25,000/-+ GST
Installment Date At the time of Enrolment 20th Oct 18 25th Jan 2019
Other Fees (Part B )
Book and Material (Mandatory fees) Rs 5,500/- + GST per participant Payable directly to FORE School of Management, New Delhi.

Program Content

  • Introductory Business Statistics (15 Hours)
  • Data Mining & Data Analytics
    • Machine Learning algorithms (51 Hours)
    • Hadoop and Kafka Eco System; Data stream processing and analysis(26 Hours)
    • NoSQL and Graph Databases(12 Hours)
    • Deep learning, AI & Computer vision (22 Hours)
  • Business Analytics Capstone (Python Oriented) (20 Hours)
  • Web Analytics (08 Hours)
  • Student Exercises/Projects

Detailed Course Content may please be seen here.
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Assessments: Based on Performance in Exercises & Projects

Tech Mahindra Growth Factories Ltd.

A - 20, Sector - 60, Noida - 201301

info@educationlanes.com

Mobile:+ 91 9975806184

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