Data Science - Internship

Introduction to Data Science

• Introduction to Data Science

• Traditional v/s Data Science Approach

• Data Science Disciplines

• Difference between and reasons behind each DS Field (Analytics & Analysis || BI/BA &

• DS & ML & AI & DL & Big Data)

• Application and Real-World Examples

• Companies Overview

• Data Science Hype

• Why Companies want it

• Overview on Data Science Pipelines

• Debunking common DS Misconceptions

• Data Science Tools and Technologies

• Career in Data Science

• Industry Expectations from Data Science role

Business Analytics with Excel

• Introduction to Excel

• Spreadsheet Environment

• Absolute and Relative Reference

• Data Sorting and Filtering

• Basic and Advance Conditional Formatting

• Excel Formulas and Functions

• Basics Data Manipulation

• Basic Function

• o Basic and Advance Date Functions

• Basic and Advance Logical Functions

• Lookup and Reference Functions

• Data Wrangling on real-world Dataset

• Excel Pivot Tables

• Intro to Tables

• Pivot Charts

• DAX functions

• Excel Visualization

• Intro to Different charts

• Dynamic charts

• Views for a worksheet

• Excel Dashboarding and VBA

• What is a Dashboard?

• How to build a Dashboard?

• Build a Dashboard

• Difference between VBA, Macros, VB, VBS

• Practical Exercise of VBA and Macros

• Overview of the Examples of attractive Dashboard

Data Visualization and storytelling with Tableau

• Data Visualization Fundamentals

• Basics of Data Visualization

• Exploratory v/s Explanatory Visualization

• Excel vs SPSS vs R vs Tableau

• Introduction to Tableau

• Tableau Environment Overview

• Tableau Desktop and Public Overview

• Connecting with Data Sources

• Managing, Organizing and Enhancing Data in Tableau

• Basic Data Wrangling in Tableau

• Creating Sets, Calculated fields, Parameters and Joins

• Use of Data Filtering and Data Blending

• Interactive Graphing and Charts

• Types of Charts in Tableau

• Waterfall Chart, Bump chart, Dual Axis chart and Scatterplots etc.

• Usage and filtration of data with charts

• Storytelling and Dashboarding in Tableau

• Designing Dashboard

• Creating Stories in Tableau

• Dashboard Layout and formatting

Introduction to Databases

• Introduction to Databases

• What is Database

• Introduction to MySQL and NoSQL

• DDL v/s DML v/s DCL v/s TCL

• Datatypes in SQL

• Basics of SQL

• Basic SQL statements (SELECT, DELETE and UPDATE)

• How to convert data into tables

• COMMIT and ROLLBACK statements

• Filtering Data using SQL

• Filter Data using the WHERE and ORDER BY Clause

• Using of Filtering Operators – IN, NOT IN, IS NULL, BETWEEN

• Regular Expression for Filtering

• Functions in Database

• Basics of Function

• Boolean Expressions and Concatenation

• String Function

• Grouping Function

• Displaying Data from Multiple tables

• Introduction to Joins and its types

• Using UNION, UNION ALL and EXPERT Clause

• Views, Sequences and Indexes in SQL

• Grouping Data and Computing Aggregates

• Introduction to Grouping

• Using GROUP BY & HAVING

• Subqueries and Nested queries in SQL

• Single-Row, Multiple-Row Subqueries

• Subqueries with ANY and ALL Operators

• Conditional Expressions using CASE Clause

• Correlated Subqueries

Python for Data Science

• Introduction to Data Science Tools

• Intro to Jupyter Notebook

• Notebook Type Interface for Data Science

• Google Colab and Kaggle Kernels

• Introduction to Kaggle and GitHub

• Overview of the Projects in Python

• Python Fundamentals

• Why Python and how it is different from the R programming language

• Variables, Identifiers and Keywords in Python

• Data Structures in Python

• Strings, Array, Lists, Tuples, Set and Dictionaries

• Python Conditionals and Loops

• If, Nested If, Indentations

• Loops in Python

• Basic Operation and Operator in Python

• Operators in Python

• OOPs Concept

• Basic Operation (String Traversal and Slicing)

• Python Functions and Classes

• Functions and its types

• Classes in Python

• Type Conversion

• Function Arguments, Recursion and creating and Lambda Functions

• Solving Basic Programs in Python

• Fibonacci Sequences

• Prime Numbers

• 0/1 Knapsack Problem

Advance Python for Data Science

• Data Wrangling using NumPy

• Introduction to NumPy Fundamentals

• NumPy Array

• NumPy Indexing and Selection

• Application and Real-world Problem solving using NumPy

• Data Wrangling using Pandas

• Introduction to Pandas Fundamental

• Data frame and Series in Pandas

• Application and real-world problem-solving using Pandas

• Python for Visualization: Matplotlib & Seaborn

• Matplotlib and Seaborn Fundamental

• Introduction to Different Plots and Charts

• Data Wrangling and Visualization on a real-world dataset