Course Details

Artificial Intelligence

Master Artificial Intelligence with Python — from data handling using NumPy and Pandas to visualization with Matplotlib & Seaborn. Build strong foundations in statistics, supervised & unsupervised learning, regression, preprocessing, tree models, and neural networks. Explore Natural Language Processing (NLP) and Generative AI tools like ChatGPT, Bard, and DALL-E.

Top Course

  • 50+ Students
  • English

What You’ll Learn?

  • Work with Python in Jupyter for AI workflows.

  • Manipulate and analyze data with NumPy and Pandas.

  • Apply statistical thinking and perform exploratory data analysis.

  • Build supervised and unsupervised models including regression.

  • Learn Generative AI basics: HuggingFace, ChatGPT, Bard, DALL-E and real-world use cases.

  • Explore Natural Language Processing (NLP) with NLTK, Spacy, Gensim, FastText.

Course content

  • 16 Sections
  • 45 - 90 Lectures
  • 45h - 90h Total Duration
Python (Internals, do's and don'ts) Architecture, Data Structure

  • Install Anaconda

  • Jupyter Notebook Overview

  • Shortcuts in Jupyter

  • Data Types

  • Variable naming rules

  • List, Tuple, Set, Dict

  • Introduction to Files and directories

  • Command prompt paths

  • Read text files with open/with

  • If, elif, else

  • For loop

  • While loop

  • ML Libraries

  • Numpy Hands-on

  • Pandas overview

  • Pandas Hands-on

  • Explore, visualize, extract insights from data

  • Matplotlib Hands-on

  • Seaborn Hands-on

  • Think statistically

  • Measures of Central Tendency

  • Measures of Dispersion

  • IQR Statistics Hands-on

  • Classification & Regression, Fine-tuning your model

  • Supervised Learning

  • Unsupervised Learning

  • Linear Regression

  • Metrics & Hands-on in Linear Regression

  • Logistic Regression

  • Metrics

  • Hands-on

  • Linear Regression

  • Metrics

  • Intro to preprocessing

  • Standardizing Data

  • Exploratory Data Analysis

  • Missing Values

  • Outliers

  • Normalization

  • Feature Scaling & Selection

  • Decision Trees

  • Bagging

  • Random Forest

  • Fundamentals of NN

  • Use data science packages, visualize, build model etc.

  • NLTK

  • Spacy

  • Gensim, FastText

  • How does generative AI work?

  • Generative AI models

  • What are Dall-E, ChatGPT and Bard?

  • What are use cases for generative AI.

This Course Includes:

  • Lifetime Access to Course

  • Internship/Project

  • Certificate of Completion

  • Interactive Quizzes

Join this Course

Course Feedback

The AI course covered machine learning, neural networks, and NLP thoroughly, giving me strong technical knowledge and project experience.

Aditi Sharma

Hands-on work with Python, NumPy, and Generative AI tools boosted my skills and confidence for real-world AI career opportunities.

Kunal Verma

Clear teaching on algorithms, deep learning, and ChatGPT integration helped me understand complex AI concepts and apply them effectively.

Sowmya

From basics to advanced AI models, the course offered structured learning, practical labs, and valuable interview-focused project guidance.

Jahnavi Roy