Become a Full Stack Business Analyst

Introduction to Python programming language with installation and basic concepts.

• Introduction to Python Programming Language (What & Why)
• Installation of Software – Anaconda
• Understanding Jupyter Notebook
• Python Basics – Syntax and Semantics
• Basic Data Types in Python
• Variables & Operators in Python
• String Operations

Master Python’s built-in data structures for efficient data handling and manipulation in Business of Full Stack.

• Tuples
• Lists
• Dictionary
• Sets
• Real world examples of List and Dictionary
• Merging multiple list and dictionary using zip function

Learn decision-making and looping constructs to control program execution flow.

• Conditional Statements (if, elif, and else)
• Loops in Python (For and While)
• Break, Continue and Pass Statements
• Nested For Loop
• Coding Exercise

Create reusable code blocks and understand advanced function concepts.

• Introduction to User Defined Function
• Difference between In Built Function and User Defined Function
• Creating user defined function
• Lambda Function
• Map, Filter and Reduce
• Coding Exercise and Practice Question

Advanced Python concepts including comprehensions, modules, and error handling.

• List Comprehension
• Dictionary Comprehension
• Import Modules and Packages in Business of Full Stack
• Exception Handling with try, except, else and finally blocks
• Coding Exercise and Practice Questions

Foundation of statistical concepts essential for data analysis and interpretation.

• Define Random Variable – Different types of Random Variables
• Introduction to Statistics
• Descriptive vs. Inferential Statistics
• Measure of Central Tendency (Mean, Median and Mode)
• Measure of Variations (Range, Variance and Standard Deviation)
• Empirical Formula to detect an outlier
• Quantiles

Learn numerical computing with NumPy arrays for efficient mathematical operations.

• Creating a NumPy Array
• In-Built functions of Numpy
• Broadcasting
• Arithmetic Operations & Statistical Functions
• Practice Questions

Master data manipulation and analysis using the powerful Pandas library.

• Creation of Series and Data Frame
• Indexing and Slicing
• Reading Data from Various sources using Pandas
• Operations on Data Frames
• Grouping and Pivoting
• Merge and append
• Practice Questions

Create compelling visualizations using Matplotlib, Seaborn, and Plotly libraries.

• Creating Charts with Matplotlib and Seaborn
• Line Chart, Histogram and Bar Graph
• Scatter Plot and Pie Chart
• Distribution Plot and Box Plot
• Heatmaps
• Plotly
• Summary of a case study data

Comprehensive data exploration techniques including web scraping and data cleaning.

• Introduction to EDA
• Data Sourcing using Web Scraping
• Scrap E-commerce data using beautiful soup
• Data Cleaning Processes Fixing Rows & Columns and Impute/Handle Missing Values
• Feature Scaling
• Fixing invalid Data Types in Business of Full Stack
• Filtering Data: Duplicate Values, Fixing Rows & Columns and Aggregate Data
• Univariate and Bi-variate Analysis

Foundation of database management and SQL programming concepts.

• Understand SQL (Structured Query Language) – What & Why?
• Installation of PostgreSQL Database and PgAdmin Tool
• RDBMS – Relational Database Management System
• DDL (Data Definition Language) Statements
• DML (Data Manipulation Language) Statements

Learn fundamental SQL operations for data retrieval and manipulation.

• Create a simple table
• Load and read the data in Business of Full Stack
• Understanding different data types
• Constraints in SQL
• Remove, Modify, Group and Arrange data using SQL commands
• Aggregate Functions, String Functions and Date-Time Functions
• Practice Questions

Master complex SQL operations including regular expressions and nested queries.

• Regular Expressions
• Syntax to SQL code with LIKE operator
• Nested Query
• Views & Indexes
• Exercise Questions using advanced SQL commands

Learn to combine data from multiple tables using various join operations.

• Inner and Outer Joins
• Left and Right Joins
• Cross Join
• Queries Involving Views and Joins
• Union, Intersect and Minus
• Practice Questions

Advanced analytical functions for complex data analysis and reporting.

• Syntax to write SQL query using Window Function
• Rank Function
• Dense Rank Function
• Difference between Rank and Dense Rankin in Business of Full Stack
• Lead and Lag Function in SQL
• Exercise Question on Window Function

Get started with Microsoft Power BI for business intelligence and data visualization.

• Scope of Power BI
• Download and Install Power BI Desktop Application
• User Interface of Power BI Desktop
• Fetching and Reading Data from Different Sources (Excel, CSV, and SQL etc.)

Master data transformation and preparation using Power Query Editor.

• Understanding Power Query Editor
• Number, Text and Date Functions in Power Query Editor
• Data Cleaning in Power Query Editor
• Append, Merge and Conditional Columns in Power Query Editor
• Working with Filter, Parameters and Sorting in Power BI Power Query Editor
• Introduction to Custom Function to Clean & Combine Files

Create compelling visual representations of data using various chart types in Business of Full Stack.

• Creating different Column Charts in Power BI
• Pie Chart, Donut Chart and Funnel Chart in Power BI
• Line Chart, Ribbon Chart and Scatter Plot in Power BI
• Creating Maps in Power BI
• Creating Tables in Power BI
• Number Cards, Text Cards and Gauge Charts in Power BI

Advanced chart customization and interactive features for better insights.

• Include & Exclude in Power BI
• Filters & Slicers in Power BI
• Basic & Conditional Formatting
• Using Drill Through in Power BI
• Using Elements & Actions in Power BI
• Formatting of Pages & Report

Learn DAX formulas for advanced calculations and data modeling.

• Introduction to Data Modelling
• Basic Date Functions – Extracting Date, Month, Day Name and Time
• Text Functions & Logical Functions
• Creating New Measures & Columns
• Calculate Time Intelligence Functions
• MTD, QTD and YTD using Quick Measures
• Filter Function, Top N Function and Summarize Function in Power BI

Deploy and share Power BI reports and dashboards in the cloud.

• Introduction to Power BI services
• Create an account on Power BI service
• Publish Report to Power BI Service
• Export Power BI Report in PPT, PDF & PBIX Format
• Creating a Final Dashboard in Power BI Service

Build web applications and deploy data analysis models using modern frameworks.

• Download and Install PyCharm
• Understanding Simple Flask App Skeleton
• Integrating HTML with Flask Web App
• Working with HTTP verbs Get and Post
• Building Web App using Streamlit
• Example of Data Analysis Model with Streamlit Web App

Version control and collaboration using Git for project management.

• Introduction to GIT
• Installation and Basic Commands
• Git Merge, Push, Checkout and Log with commands
• Resolving GIT branch merge conflict

Deploy and scale applications using Amazon Web Services cloud platform.

• Introduction to Cloud Computing
• Introduction to AWS
• Create an AWS account
• Billing Cost Management & Cost Explorer
• Introduction to EC2(Elastic Cloud Computing)
• Creating EC2 and Project Pipeline
• End to End Data Analysis Project Deployment using AWS

Hands-on projects across different domains to build practical expertise and portfolio.

• Build an End to End Quiz Application with Python
• Scrap YouTube Data using API for Analysis and Visualisation with Python
• Analysing IMDB Movie Dataset
• Analyse the RSVP movie dataset and draw meaningful insights
• Create a dynamic sales performance analysis dashboard using Power BI
• Analysing Multiple Stocks using Power BI Dashboard (Finance Domain)
• Credit Card Default Analysis to minimize risk (Banking Domain)
• End to End Data Analysis Project Deployment using AWS

Real-world case studies from various industries for practical learning experience.

• Analysing Real-World E-commerce Sales Data
• Understanding Risk Analytics in Banking and Financial Services using EDA
• Analysing Customer Behaviour using SQL – A Real Life Data Analyst Case Study
• Analysing Bank Customer Relationship for forecast and future developments

Comprehensive career preparation and industry-ready certification upon completion.

Job Roles:

• Business Analyst
• Data Analyst
• Business Intelligence Developer
• Data Scientist
• SQL Developer
• Power BI Developer
• Analytics Consultant
• Reporting Analyst

Industries:

• E-commerce and Retail
• Banking and Financial Services
• Healthcare and Pharmaceuticals
• Technology and Software
• Manufacturing and Supply Chain
• Consulting and Professional Services
• Government and Public Sector
• Media and Entertainment

Career Support in Business of Full Stack:

• Interview Questions Practice for Business Analyst Role (Google, Amazon, Microsoft)
• Resume Review and Portfolio Development
• Mock Interviews and Technical Assessment Preparation
• Industry Networking and Job Placement Assistance
• Continuous Learning Resources and Updates
• Alumni Network and Mentorship Programs