Topics:

• Brief history of database
• Commercial and open source SQL products
• Data models
• Introduction to SQL

Learning Objectives:

After completing this module, students will be able to understand about:

• Database development history
• Different types of data models
• Key component of database and table

Skills
RDBMS

Subskills
Basics

Core Competencies

• Database history
• Types of SQL Products
• Types of Data Models
• Types of SQL Commands

Delivery Type:
Theory

Hands-on workshop
No

Home Assignment
No

Topics:

• Create Command
• Drop Command
• Truncate Command
• Alter Command
• Rename Command

Learning Objectives:

After completing this module,

• Student will be able to apply DDL operations like create, drop, truncate, alter and rename on a table

Skills
SQL

Subskills
Basics

Core Competencies

• Create table and database
• Delete table columns, table
• Delete existing information from table
• Change table attributes
• Rename table attributes

Delivery Type:

Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Insert Command
• Update Command
• Delete Command

Learning Objectives:

After completing this module,

• Student will be able to apply DML operations like insert, update and delete records from/to a table

Skills
SQL

Subskills
Basics

Core Competencies

• Insert values in the table as rows
• Update rows
• Delete rows

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Select Query
• Filtering Records
• Where Clause Predicates
• Sorting Records

Learning Objectives:

After completion of this module students will be able to:

1. Fetch information from the tables using the select query
2. Filter records from the table using While clause
3. Sort records

Skills
SQL

Subskills
Basics/Intermediate

Core Competencies

• DQL query
• Wildcard Filtering
• Conditional Filtering
• Sorting Records

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• count() Function
• sum() Function
• avg() Function
• min() Function
• max() Function
• Distinct Keyword
• Group By Clause
• Summarizing Values

Learning Objectives:

After completion of this modules students will be able to:

1. Perform aggregate operations table columns
2. Fetch outcome using grouped queries (GROUP BY)
3. Summmarize information using aggregate function with the group by clause

Skills
SQL

Subskills
Intermediate

Core Competencies

• Table records aggregating functions

• Aggregate functions with Grouped Queries

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Inner Join
• Left Join
• Right Join
• Full Outer Join
• Self Join

Learning Objectives:

This module will help students to use join clauses to gather information in a single table from multiple tables.

Skills
SQL

Subskills
Intermediate

Core Competencies

• Combine records from two or more tables

• Combine records from same tables

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Jupyter Environment
• Pseudocode
• Using Print ()
• Wrong usage of print()
• Variables
• Creating a variable
• Reassign a variable
• Multiple variable assignment
• Data Types
• Finding data types of variables
• Data type conversion (Implicit)
• Data type conversion (Explicit)
• Arithmetic Operations
• String Operations
• Boolean Operations
• String handling
• Concatenation
• if-else, loops

Learning Objectives:

Learn the basics of Python programming. This module will hand-hold a non-programmer to the programming world.

After completing this module you will be able to:

• Write basic Python syntaxes
• Understand basic Python data types
• Write logical conditions
• Perform data type conversion

Skills
Python

Subskills
Basics

Core Competencies

• Installation
• Print() Function
• Python Variables
• Data Types
• Python Operators
• String Operations
• Python Control Flow

Delivery Type:

Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• What is Tuple?
• Creating tuple
• Tuple operations
• Tuple: In-built function
• What is a list?
• Creating a list
• List operations
• List: In-built functions
• List Joins
• What is a set?
• Creating a set
• Set operations
• Set: In-built functions
• What is a dictionary?
• Dictionary operations
• Dictionary in-built functions
• Conditional statements: if else
• Conditional statements: nested if

Learning Objectives:

This module will introduce Python objects that are required in the field of data science.

After completing this module you will be able to:

• Understand various Python objects like Lists, Tuple, Dictionary & Sets
• Perform various operations on Python Objects
• Learn various functions associated with each of the Python objects"

Skills
Python

Subskills
Basics/Intermediate

Core Competencies

• Tuple Basics
• Tuple Operations
• List Basics
• List Operations
• Set Basics
• Set Operations
• Dictionary Basics
• Dictionary Operations
• Python Flow Control

Delivery Type:

Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• What is python numpy
• Functions to create array
• Numpy operations - dtypes, size, shape, reshape, itemsize
• Indexing array
• Slicing array
• Arithmetic operations on array
• Arithmetic functions on array - sum(), min()
• Concatenation of Arrays

Learning Objectives:

This module introduces Numpy array for numerical computation.

After completing this module you will be able to:

• Learn what is a Numpy array
• Create Numpy arrays
• Describe a Numpy array in terms of dimensions & size
• Explain the difference between a Numpy array & a Python List"

Skills
Python

Subskills
Basics/Intermediate

Core Competencies

• Intro to Numpy Library
• Intro to array
• Array Operations

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Python pandas
• Data structures
• What is series?
• Creating a series
• Manipulating series
• Usage if .loc and .iloc
• What is a dataframe?
• Creating a dataframe

Learning Objectives:

This module introduces Pandas objects like Series & Dataframes

After completing this module you will be able to:

• Learn what is a series object
• Perform various operations on a series object
• Learn what is a dataframe
• Perform various operations on a dataframe"

Skills
Python

Subskills
Basics/Intermediate

Core Competencies

• Intro to Pandas
• Intro to Series
• Series Operations
• Intro to Dataframes

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Manipulating dataframes
• Indexing a dataframe
• Read data from various sources
• Concatenate the dataframes
• Merge using inner join
• Merge using outer join
• Merge using right join
• Merge using left join
• Reshape using melt() function
• Check for duplicates

Learning Objectives:

This module takes you to the next level of operations on dataframes

After completing this module you will be able to:

• Concatenate multiple dataframes vertically & horizontally
• Understand various kind of joins like inner join, outer join, left join & right join
• Learn the differences between concat, merge

Skills
Python

Subskills
Advanced

Core Competencies

• Dataframe Operations

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Plots using Matplotlib
• Line plot
• Scatter plot
• Bar plot
• Pie plot
• Histogram
• Box plot
• Plots using Seaborn
• Strip plot
• Pair plot
• Distribution plot
• Count plot
• Heatmap

Learning Objectives:

This module takes you to the world of visualization that is necessary for analyzing data from data science perspective

After completing this module you will be able to:

• Learn various kinds of plots
• Understand which plot to be used for specific analysis
• Learn using 2 key libraries - Matplotlib & Seaborn"

Skills
Python

Subskills
Advanced

Core Competencies

• Matplotlib Library

• Bivariate Plot

• Univariate Plot

• Univariate Plot, Bivariate Plot

• Seaborn Library

• Multivariate Plot

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes

Topics:

• Summary Statistics
• Missing Value Treatment
• Dataframe analysis using groupby()
• Advanced Data Explorations

Learning Objectives:

This module introduces the fundamentals of data exploration with deeper insights

After completing this module you will be able to:

• Know various techniques to analyse your data from various angles
• Summarize important Statistics
• Know advanced techniques to churn deeper insights
• Learn missing value imputation strategies"

Skills
Python

Subskills
Advanced

Core Competencies

• Five point summary of data

• Missing Value Analysis

• Dataframe Operations

Delivery Type:
Theory + Workshop

Hands-on workshop
Yes

Home Assignment
Yes