Foundation Courses
Introduction and
Programming
Statistics and
Visualization
Advance Methods
Simplify complex spreadsheets
Use advanced functions of MS Excel
Apply visual elements and advanced formulas to a
worksheet
Enhance spreadsheets with templates, charts, graphics
and Excel formulas
Automate common tasks, apply advanced analysis
techniques to complex data sets
Collaborate on worksheets with other users
Problem-solving approaches
Case studies
Case study application
Modules
A-1 Basic Statistics
A-2 Advanced Statistics
A-3 Data Analysis In Excel -I: Pivots and
LookUps - Hands On
A-4 Data Analysis In Excel -II: Building &
Using Macros for Analytics - Hands On
B-1 SQL Programming Essential, Database
Design and Creation
B-2 MySQL Workbench and Querying
B-3 Window Functions - Hands On
B-4 Query Optimization - Hands On
C-1 Big Data and Data Analytics
C-2 Big Data Storage and Processing - Hadoop
C-3 Cloud Computing
C-4 Data Modelling Methods and Components
C-5 Problem Solving Using Data Modelling
D-1 Introduction to Tableau & Power BI
D-2 Data Modelling
D-3 Calculations
D-4 Visualizations
D-5 Automation
D-6 Distribution
E-1 Python Programming Essentials I -
Variables, Expressions, and Data Structures, Conditionals,
Iterations, Strings, Exceptions
E-2 Introduction to Statistics & Probability,
Probability Distributions
E-3 Brief Introduction to Class / Object
Oriented Programming
E-4 Python Programming Essentials II -
Functions and Control Statements
E-5 Python Libraries for Data Science -
Pandas
E-6 Python Libraries for Data Science -
NumPy, other Modules like datatime, Matplotlib
F-1 Machine Learning Types
F-2 Introduction to key Machine Learning
Models
F-3 Leaning the Machine Learning Life Cycle
F-4 Building Machine Learning Models Python
Program Outcomes
Data Preparation :
Structuring data, sourcing the data sets, managing the planning, design and execution of analysis, and helping communicate, interpret and implement the results
Data Driven Strategy:
Generate meaningful business insights that define strategy, processes and key performance indicators according to industry best practices to monitor the overall performance against the competitors.
Customer Analytics:
Understanding your customer better through segmentation, identification and targeting, and supporting effective marketing strategies and campaigns.
Live Dashboards:
Gaining access to real-time, actionable customer and market information to make informed and multi-layered business decisions.
Risk Analytics:
Identify, quantify, and prevent potential financial issues by using techniques such as predictive models, user behavior analysis, and audit logs.
Process Design:
Use data collection, analyzing, & modeling techniques to improve the efficiency, effectiveness, and quality of the business functions that can help in optimizing resources, enhancing innovation, and creating value for the organization.
Schedule
Week 1 |
Foundation Courses & Orientation |
---|---|
Week 2-15 |
Live Sessions on Core Modules |
Week 16 |
Capstone Project & Masterclass |