Online Course on Unlocking Business Challenges Using Zero-Code Analytics (3:0)

Objectives

Apart from the basics of machine learning concepts, Participants would be introduced to real-life scenarios by case-study method, where Statistical and Machine Learning concepts can be applied to solve business/data problems. This course takes a deep dive to explain and interpret the machine learning output in the context of the case study.
There would be a bridge course on basic concepts of statistics which can be taken by students who would like to refresh their knowledge. It’s recommended that all students take it to enable faster learning during course sessions.

Syllabus

Introduction of statistical inferences, Exploratory data analysis, Data preprocessing, hypothesis, machine learning, different types of machine learning (supervised: Regression, classification, decision tree, random forest, unsupervised learning: clustering, factor analysis, PCA), Overview Neural learning.

Target Group

Working professionals (IT/ITES/Pharma/Health/Fintech/Banking/E-Commerce/Real Estate/PSUs/Energy/Sustainability), Faculties of STEM and commerce stream, Pharma, Healthcare, PG/Graduates, Engineering, Management, Mathematics, Statistics, Economics

Who Can apply?

BE/BTech, ME/MTech, Msc/MS (Data Science), Computer Science, Mathematics, Statistics, MCA, MA in economics, MBA

Pre-requisites
Basic knowledge of statistics, mathematics

Reference Books

1. Hands-On Machine Learning with Scikit-Learn and TensorFlow Publisher(s): O’Reilly Media, Inc. Author : Geron Aurelien
2. Data Science from Scratch. Publisher(s): O’Reilly Media, Inc. Author: Joel Grus
3. Complete Business Statistics | 7th Edition: Publisher(s): McGraw Hill, Author: Amir Aczel (Author), Jayavel Sounderpandian (Author), P Saravanan (Author)
4. Marketing Analytics: Data-Driven Techniques with Microsoft Excel : Publisher(s): Willey, Author: y Wayne L. Winston