Data Science with AI – Proffesional IIT-T Certificate Program

About Course

Educhithra’s 3-Month Data Science with AI Program covers everything from the basics to advanced AI. The curriculum includes Python programming, statistics, data analysis, and visualization. You’ll learn machine learning, deep learning with TensorFlow, and natural language processing (NLP) for real-world AI applications. The program also trains you in Power BI and SQL for business insights, ending with a capstone project that integrates all your learning into a practical, industry-relevant solution.

In Educhithra’s Data Science with AI Program, learners gain hands-on expertise in Python programming, data analysis, and visualization using tools like Pandas, NumPy, and Power BI. The program covers the complete data science pipeline — from data preprocessing and statistical modeling to building predictive and deep learning models using Machine Learning, Neural Networks, and Natural Language Processing. Students work on real-world AI projects in domains like healthcare, finance, and e-commerce, applying their skills to solve practical problems. The program concludes with a capstone project, career guidance, and industry mentorship to help learners become job-ready data science professionals.

Course Content

Module 1: Introduction to Data Science & AI

Day 1

53:25
Day 2

45:34
Day 3

41:46
Day 4

48:13
Day 5

39:40

Module 2: Python for Data Science & AI

Module 3: Statistics & Probability

Module 4: Data Visualization

Module 5: Machine Learning Fundamentals

Module 6: Advanced Machine Learning &AI

Module 7: Deep Learning & Neural Networks

Module 8: Natural Language Processing (NLP)

Module 9: AI Projects & Applications

Module 10: Capstone Project & Industry Practices

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About Course

What Will You Learn?

Course Content

Module 1: Introduction to Data Science & AI

Day 1

Day 2

Day 3

Day 4

Day 5

Module 2: Python for Data Science & AI

Python basics and libraries (Jumpy, Pandas)

Data manipulation and analysis

Handling datasets and basic preprocessing

Module 3: Statistics & Probability

Descriptive and inferential statistics

Probability theory and distributions

Hypothesis testing and data summarization

Module 4: Data Visualization

Matplotlib, Seaborne, and Polly

Creating charts, plots, and dashboards

Storytelling with data

Module 5: Machine Learning Fundamentals

Supervised vs. Unsupervised

Regression and classification algorithms

Model evaluation metrics

Module 6: Advanced Machine Learning &AI

Decision Trees, Random Forest, and

Clustering and Dimensionality

Introduction to Neural Networks

Module 7: Deep Learning & Neural Networks

Artificial Neural Networks (ANN) basics

Convolution Neural Networks (CNNa)

Recurrent Neural Networks (RNN)

Module 8: Natural Language Processing (NLP)

Sentiment analysis and chat bots

Sentiment analysis and chat bots

Language models and AI applications

Module 9: AI Projects & Applications

Real-world case

Predictive modeling and recommendation

AI in healthcare, finance, and e-commerce

Module 10: Capstone Project & Industry Practices

End-to-end AI project development

Data collection, cleaning, modeling, and deployment

Best practices, ethics, and career guidance

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Educhithra