BIG DATA ANALYTICS For BUSINESS & MANAGEMENT
Tech Mahindra along with FORE School of Management, New Delhi will prepare the future Big Data Engineers to fulﬁll the market demand.
6 Months -
Total 154 Hrs of Learning
Saturday & Sunday
10:30 am - 01:30 pm
3 Easy EMI
Why to Take
BIG DATA ANALYTICS
Applications of Big Data transcend disciplines. Use of predictive analytics pervades diverse disciplines as oil and gas, marketing and sales, sports, molecular biology, drug-designing, waste management, finance and the list is 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
WHO SHOULD ATTEND?
DATA SCIENTISTS/ DEVELOPERS
Lecturers and Professors for extending the horizon of their knowledge through deepening their research skills.
Ambitious Executives (from Private/Public sectors) with 0-2 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
Techniques taught to them will have applications in a broad array of disciplines.
Why Education Lanes
for 6 Months
3 Easy EMI Option
Interactual Learning Platform
24 Hours Support
Bring Education to your Home
We strongly believe that a course in data analytics can only be practice-basedrather than theory based. The teaching pedagogy will be like this: First, thetechnique/algorithm is conceptually explained without getting into mathematicsand then a project is undertaken to implement the technique. Datasets forimplementation are made available in advance and so also a copy of codewe need to execute. The code is numbered and copiously commented uponso that long after the lecture has finished, students can go back through thecode/comments and refresh their knowledge. During the lecture, we executethis code, line-by-line and explain the steps. At his/her end, the student alsoexecute the same code and may seek clarification. Consequently, results areavailable at our end as also on Students’ Laptop.
6 Months -
154 Hrs of Learning
Introduction to Business Statistics
Business Analytics Capstone
Data Mining & Data Analytics
Students Exercise & Project
**Above Modules are sub-divided into further more modules.
Prof. Ashok Kumar Harnal
Prof. Ashok Kumar Harnal: Graduated from IIT Delhi in Electronics and Communication; M. Phil with Distinctionfrom Punjab University, Chandigarh, and MA (Economics) from Punjabi University. Expert in Big Data, DataAnalytics and Deep Learning, both on the technology side as also on Analytics side. Extensively taught faculty andstudents on the subject of big data technology and analytics. Has been associated with University of California,Riverside, US, in one of the Executive Education programs on Big Data and Data Analytics for last three years.Participated in various machine learning projects with real world data in areas of business, environment, marketingand advertisement. Conceived, planned and implemented in Defence Estates three country-wide informationsystems: a) Raksha Bhoomi to computerize land records; b) Knowledge Management of land-title relatedfiles/maps in all Defence Estates offices; and c) Setting up of a Disaster Management organization, Archival Unitand Resource Center, at Delhi and at Pune for safe storage of land-title related records in paper, digital & microfilmforms. Authored two books: one on Programing Games on Computers and the other on Linux Applications andAdministration; both books have been published by Tata McGraw-Hill.
Prof. Kemal Oflus, Professor at UCR: Capstone Project Faculty convering Python module, Ex-rocket scientist. Highlymotivated and versatile data scientist with fifteen plus years of proven analytics performance. Skilled at building effectiveand productive working relationships with customers, team members, executive management. Excellent time management,negotiation, interpersonal and presentation skills. A talent for analyzing problems, developing simplified procedures, andfinding innovative solutions those improve operating efficiency and lower costs for customer. Successful in bringingmethods long have been used in engineering and scientific communities to business customers and decision makers.
Prof. Kemal Oflus
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