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Batch Date: July 22nd @7:00PM

Faculty: Mr. Venkat (15+ Yrs Of Exp,..)

Duration: 3 Months 15 Days

Venue :
DURGA SOFTWARE SOLUTIONS,
Flat No : 202, 2nd Floor,
HUDA Maitrivanam,
Ameerpet, Hyderabad - 500038

Ph.No: +91 - 8885252627, 9246212143, 80 96 96 96 96

Syllabus:

DATA ANALYTICS with AI/ML
(PYTHON + SQL + POWER BI + EXCEL + STATISTICS + AI + ML)

Module 1: Python Programming

Python Fundamentals

• Introduction to Python
• Installation & IDE Setup
• Variables
• Data Types
• Operators
• Input & Output
• Comments
• Type Casting

Control Statements

• If
• If Else
• Nested If
• Loops
• Break
• Continue
• Pass

Functions

• User Defined Functions
• Lambda Functions
• Recursion
• Scope
• Arguments

Data Structures

• Lists
• Tuples
• Dictionaries
• Sets
• Strings

File Handling

• Read Files
• Write Files
• CSV Files
• JSON Files

Exception Handling

• Try
• Except
• Finally
• Custom Exceptions

Object Oriented Programming

• Classes
• Objects
• Inheritance
• Polymorphism
• Encapsulation
• Abstraction

Advanced Python

• Modules
• Packages
• Regular Expressions
• List Comprehension
• Iterators
• Generators
• Decorators
• Virtual Environments
• Git & GitHub Basics

Module 2: Advanced Excel for Data Analytics

Excel Basics

• Workbook
• Worksheets
• Tables

Data Cleaning

• Remove Duplicates
• Text to Columns
• Flash Fill
• Data Validation

Advanced Formulas

• IF
• Nested IF
• IFS
• COUNTIF
• SUMIF
• SUMIFS
• INDEX
• MATCH
• XLOOKUP
• VLOOKUP
• HLOOKUP
• OFFSET
• INDIRECT

Data Analysis

• Conditional Formatting
• Pivot Tables
• Pivot Charts
• Slicers
• Timelines

Dashboard Development

• Interactive Dashboards
• KPI Reports
• Business Reports

Module 3: SQL for Data Analytics

Database Fundamentals

• RDBMS
• ER Diagram
• Database Design

SQL Commands

• DDL
• DML
• DCL
• TCL

Queries

• SELECT
• WHERE
• ORDER BY
• GROUP BY
• HAVING

SQL Functions

• Aggregate Functions
• String Functions
• Date Functions
• Numeric Functions

Joins

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

Advanced SQL

• Subqueries
• Common Table Expressions (CTE)
• Views
• Indexes
• Stored Procedures
• Window Functions
• Ranking Functions

Module 4: Statistics for Data Analytics

• Types of Data
• Measures of Central Tendency
• Measures of Dispersion
• Probability
• Probability Distributions
• Sampling
• Hypothesis Testing
• Confidence Interval
• Correlation
• Covariance
• Linear Regression
• A/B Testing

Module 5: Data Analysis with Python

NumPy

• Arrays
• Matrix Operations
• Broadcasting

Pandas

• Series
• DataFrames
• Merge
• Join
• GroupBy
• Pivot
• Apply

Data Cleaning

• Missing Values
• Duplicate Removal
• Outlier Detection
• Encoding
• Scaling

Exploratory Data Analysis

• Univariate Analysis
• Bivariate Analysis
• Multivariate Analysis

Data Visualization

• Matplotlib
• Seaborn
• Business Charts
• Dashboard building
• Reports generation

Module 6: Power BI

Power BI Desktop

• Interface
• Data Import
• Data Transformation

Power Query

• Cleaning
• Merging
• Append
• Parameters

Data Modelling

• Relationships
• Star Schema
• Snowflake Schema

DAX

• Measures
• Calculated Columns
• Time Intelligence
• KPI

Dashboards

• Interactive Reports
• Business Dashboards
• Publishing Reports

Power BI Services

Module 7: Machine Learning with Python

Introduction

• AI
• Machine Learning
• Deep Learning
• Applications

Data Preprocessing

• Feature Engineering
• Encoding
• Scaling

Supervised Learning

Regression

• Linear Regression
• Polynomial Regression
• Ridge
• Lasso

Classification

• Logistic Regression
• Decision Trees
• Random Forest
• KNN
• Support Vector Machine
• Naive Bayes

Unsupervised Learning

• K-Means
• Hierarchical Clustering
• DBSCAN
• PCA

Model Evaluation

• Accuracy
• Precision
• Recall
• F1 Score
• ROC-AUC
• Cross Validation

Module 8: Generative AI for Data Analysts

Introduction to AI

• Artificial Intelligence
• Large Language Models

Prompt Engineering

• Prompt Design
• Prompt Optimization

ChatGPT for Analysts

• Data Cleaning
• Formula Generation
• SQL Generation
• Python Code Generation

AI Tools

• OpenAI Models
• Open Source LLMs
• Hugging Face

Retrieval-Augmented Generation (RAG)

• Vector Databases
• Embeddings
• Document Search

AI Agents

• Agent Concepts
• Business Automation

Module 9: Business Case Studies

Students will solve Real-World Business Problems in:

• Sales Analytics
• HR Analytics
• Marketing Analytics
• Healthcare Analytics
• Banking Analytics
• Finance Analytics
• E-Commerce Analytics
  

Module 10: Capstone Projects

Students will complete three End-to-End Projects:

Project 1

Sales Performance Dashboard

• Excel
• SQL
• Power BI
  

Project 2

Customer Churn Prediction

• Python
• Machine Learning

Project 3

AI-Powered Business Insights Chatbot

• OpenAI
• RAG
• Power BI

Bonus Modules

• Resume Building
• LinkedIn Profile Optimization
• Git & GitHub
• Interview Preparation
• Portfolio Development
• Freelancing Guidance
• Topic wise Assignments
• Topic wise Projects
• Weekend Tests
• Handson Practice
• Interview Questions discussion

Learning Outcomes

Upon completion, learners will be able to:

• Perform end-to-end data analysis using Python, SQL, Excel, and Power BI.
• Clean, transform, visualize, and interpret complex datasets.
• Build interactive business dashboards and reports.
• Apply statistical techniques to solve business problems.
• Develop predictive Machine Learning models using Scikit-learn.
• Use Generative AI to automate analytics workflows and enhance productivity.
• Complete industry-level projects and build a strong professionalportfolio
• Prepare confidently for Data Analyst, Business Analyst, and Junior AI/ML roles.