Data Science with Gen AI

4.7
Medium
12 Weeks

Data Science with Gen AI

Data Science and Generative AI are among the most sought-after technologies in today’s digital world. Organizations across industries are leveraging data-driven insights and AI-powered automation to make smarter decisions, improve customer experiences, and drive innovation.

This comprehensive training program is designed to equip learners with the skills needed to become successful Data Scientists and AI Professionals. The curriculum combines Data Science fundamentals, Machine Learning, Deep Learning, Natural Language Processing (NLP), Generative AI, and real-world projects.

The program focuses on:

  • Data Analysis & Visualization
  • Statistics & Mathematics
  • Machine Learning & Deep Learning
  • Natural Language Processing
  • Generative AI & Large Language Models (LLMs)
  • AI Automation & Real-Time Applications
  • Industry Projects & Case Studies

Who Can Join This Course?

Suitable for:

  • Students
  • Fresh Graduates
  • Data Analysts
  • Software Developers
  • Working Professionals
  • Career Transition Candidates

No prior AI experience is required. Basic computer knowledge is sufficient

Training Methodology

Course Completion Certificate

Certification

  • AI Engineer Professional Certificate
  • Generative AI & Agentic AI Certificate
  • Capstone Project Certificate

Career Opportunities After Course

Course Curriculum

Data Science Fundamentals

  • What is Data Science?
  • Data Science Lifecycle
  • Data-Driven Decision Making
  • Applications of Data Science

Introduction to Artificial Intelligence

  • AI Fundamentals
  • Machine Learning vs Deep Learning
  • AI Use Cases Across Industries

Industry Applications

  • Banking & Finance
  • Healthcare
  • Retail & E-commerce
  • Manufacturing
  • Marketing Analytics

Data Science Project Lifecycle

  • Business Understanding
  • Data Collection
  • Data Preparation
  • Modeling
  • Evaluation
  • Deployment

Python Fundamentals

  • Variables & Data Types
  • Operators
  • Conditional Statements
  • Loops
  • Functions

Object-Oriented Programming

  • Classes & Objects
  • Inheritance
  • Encapsulation
  • Polymorphism

Data Structures

  • Lists
  • Tuples
  • Dictionaries
  • Sets

File Handling

  • CSV Files
  • JSON Files
  • Excel Files

Practical Exercises

    • Business Data Processing
    • Automation Scripts
    • Data Manipulation Programs

Statistics Fundamentals

  • Mean, Median, Mode
  • Variance & Standard Deviation
  • Percentiles & Quartiles
  • Probability Concepts

Inferential Statistics

  • Sampling Techniques
  • Hypothesis Testing
  • Confidence Intervals

Mathematics for Data Science

  • Linear Algebra Basics
  • Matrices & Vectors
  • Probability Theory
  • Calculus Fundamentals

Business Analytics Applications

  • Trend Analysis
  • Forecasting Concepts
  • Statistical Decision Making

NumPy

  • Arrays
  • Mathematical Operations
  • Statistical Functions
  • Broadcasting

Pandas

  • DataFrames
  • Data Cleaning
  • Data Transformation
  • Missing Value Handling
  • Merging Datasets

Exploratory Data Analysis (EDA)

  • Data Profiling
  • Correlation Analysis
  • Feature Analysis

Practical Labs

  • Customer Data Analysis
  • Sales Data Analysis
  • Employee Data Analysis

Visualization Fundamentals

  • Importance of Data Visualization
  • Choosing the Right Chart

Matplotlib

  • Line Charts
  • Bar Charts
  • Pie Charts
  • Histograms

Advanced Visualization

  • Scatter Plots
  • Heat Maps
  • Correlation Matrix

Dashboard Development

  • Business KPI Visualization
  • Interactive Reports

Case Studies

  • Marketing Dashboard
  • Sales Performance Dashboard

Database Fundamentals

  • Relational Databases
  • Database Design Concepts

SQL Queries

  • SELECT Statements
  • Filtering Data
  • Sorting Data

Advanced SQL

  • Joins
  • Subqueries
  • Views
  • Window Functions

Business Use Cases

  • Customer Analysis
  • Revenue Analysis
  • Product Performance Analysis

ntroduction to Machine Learning

  • ML Workflow
  • Training & Testing Data
  • Model Evaluation

Data Preprocessing

  • Missing Value Treatment
  • Feature Scaling
  • Encoding Techniques

Supervised Learning

  • Regression Models
  • Classification Models

Model Evaluation Metrics

  • Accuracy
  • Precision
  • Recall
  • F1 Score
  • ROC Curve

Regression Algorithms

  • Linear Regression
  • Multiple Regression
  • Polynomial Regression

Classification Algorithms

  • Logistic Regression
  • Decision Trees
  • Random Forest
  • KNN
  • SVM
  • Naïve Bayes

Unsupervised Learning

  • K-Means Clustering
  • Hierarchical Clustering
  • PCA

Model Optimization

  • Hyperparameter Tuning
  • Cross Validation

Neural Network Fundamentals

  • Artificial Neural Networks
  • Activation Functions
  • Backpropagation

TensorFlow & Keras

  • Model Building
  • Model Training
  • Model Evaluation

Deep Learning Applications

  • Image Recognition
  • Prediction Models

Convolutional Neural Networks (CNN)

  • CNN Architecture
  • Image Classification

NLP Fundamentals

  • Text Processing
  • Tokenization
  • Stop Words Removal
  • Lemmatization

NLP Techniques

  • Bag of Words
  • TF-IDF
  • Word Embeddings

NLP Applications

  • Sentiment Analysis
  • Text Classification
  • Spam Detection
  • Chatbot Development

Generative AI Fundamentals

  • Introduction to Generative AI
  • Evolution of AI Models
  • LLM Architecture Overview

Prompt Engineering

  • Effective Prompt Design
  • Prompt Optimization
  • Chain-of-Thought Prompting
  • Role-Based Prompting

Large Language Models

  • GPT Models
  • Transformer Architecture
  • Embeddings Concepts

Generative AI Applications

  • Content Generation
  • Business Reporting
  • AI Assistants
  • AI-Based Research

AI Tools

  • ChatGPT
  • AI Coding Assistants
  • AI Productivity Tools

Responsible AI

  • Ethics in AI
  • Bias & Fairness
  • AI Governance

Business Automation

  • AI-Powered Workflows
  • Document Automation
  • Email Automation

AI for Analytics

  • Automated Insights Generation
  • Report Creation
  • Dashboard Narratives

No-Code/Low-Code AI Solutions

  • Workflow Automation Platforms
  • AI Integrations

Module 13: Model Deployment & MLOps Fundamentals

Model Deployment Concepts

  • Model Serialization
  • API Development Basics

Streamlit Applications

  • Building Data Science Apps
  • Interactive User Interfaces

Deployment Overview

  • Cloud Deployment Concepts
  • Monitoring & Maintenance

MLOps Fundamentals

  • Version Control
  • Model Lifecycle Management

📊 Sales Forecasting System

Predict future sales using historical business data.

🛒 Customer Segmentation Project

Identify customer groups using clustering techniques.

🏦 Loan Approval Prediction

Build a classification model for financial decision-making.

📧 Email Spam Detection

Create an NLP-based spam classification system.

😊 Sentiment Analysis Engine

Analyze customer feedback and social media reviews.

🤖 AI-Powered Business Assistant

Develop a Generative AI assistant for business queries.

📈 Executive Business Dashboard

Create a complete analytics solution using visualization tools.