MIS Cum Data Analysis Course with Free Data Science Certification 

Introduction to Excel

Mathematical Functions

Date and Time Function

Text Functions & Data Validation

Statistical Function & Other Functions

Logical Functions

Lookup & Reference Functions

Pivot Table – MIS, Data Analysis & Visualization

Data Collection Method

Analysis Single/Multidimensional Analysis

Advanced Dashboard in Excel

Two Live Report Development in Advanced Excel:-(Real World Data)

Introduction to Programming Introduction to logical thinking flowcharts & algorithms

Complete Review of the VBA Language (Subs, Functions, Variables, Arrays, Loops, Logic…etc.)

Excel VBA Power Programming For VBA Macros

Overview of Using User forms To Create Business Wizards

Connection between Excel VBA & other platforms

Testing and Debugging Your Code

Effective Error Handling

Automation Development Reports & Live Projects

Introduction to SQL

Explaining SQL Strings

Complete SQL in a Class

Numbers and SQL

Fundamentals of SQL

SQL Functions and Clause

How Relationships Work in SQL

Triggers in SQL

What are Subselects and Views in SQL

Maintaining SQL Server Database

SQL Server Job Creation

MS Power BI ? BI & Data Visualization

Module 1 – Getting Started with Tableau

Module 2 – Connecting to The Data

Module 3 – Visual Analytics

Module 4 – Developing First Bar Char

Module 5 – Time Series, Maps and Aggregation

Module 6 – First Dashboard

Module 7 – Blending Data and Dual Axis Charts

Module 8 – Table Calculation and Storytelling

Module 9 – Data Preparation

R Programing ? BI & Data Visualization

Module 1- Introduction to Business Analytics

Module 2- Introduction to R

Module 3- R Programming

Module 4 – R Data Structure

Module 5 – Apply Functions

Module 6 – Apply Functions

Module 7 – Apply Functions

Module 8 – Hypothesis Testing I

Module 9 – Hypothesis Testing II

Module 10 – Regression Analysis

Module 11 – Classification

Module 12 – Clustering

Module 13 – Association

Module 1 – Introduction to Python

Module 2 – Programming with Python

Module 3 – Flow Control

Module 4 – Sequence Data

Module 5 – Functions

Module 6 – Errors and Exception Handling

Module 7 – Modules

Module 8 – Importing and Exporting Data

Module 9 – Data Manipulation and Data Analysis

Module 10 – Data Structures and Regular Expressions

Module 11 – Live Practice Sessions

Introduction to Python Programming for Data Analysis:-

Data Exploration

Supervised Learning

Advanced Unsupervised Learning

Introduction to Text processing

Introduction to Deep Learning

Reference Data for running example

Dimensionality Reduction + Linear Transformation

Machine Learning Concepts

Framework