Artificial Intelligence (AI) Course in Pune

Date	Mode of Class	Batch Form	Time	Status	Action
Wednesday, September 10, 2025	Online/Classroom	Weekdays	6:30 PM IST	Batch Full	Enrollment Closed →
Wednesday, September 17, 2025	Online/Classroom	Weekdays	6:30 PM IST	Only 1 Seat AvailableMax intake limit is 10	Enrollment Open →
Wednesday, September 24, 2025	Online/Classroom	Weekdays	8:00 AM IST	Only 5 Seats AvailableMax intake limit is 10	Enrollment Open →
Saturday, September 13, 2025	Online/Classroom	Weekends	10:00 AM IST	Only 2 Seats AvailableMax intake limit is 10	Enrollment Open →

Artificial Intelligence Course

Course Overview

Enroll in our Artificial Intelligence course at Python Training Institute in Pune, located in Kharadi, the heart of Pune’s IT hub. This program is designed for beginners and professionals, covering Python, machine learning, deep learning, and NLP to build advanced AI models.

With hands-on projects like predictive models and chatbot applications, and partnerships with top Pune-based companies like Infosys and TCS, our course ensures you’re job-ready in 90 days. Earn an industry-recognized certification and benefit from our 100% placement assistance.

What You'll Learn

Core Python for AI development, including data structures and functions.
Machine learning with scikit-learn for predictive modeling.
Deep learning with TensorFlow and PyTorch for neural networks.
NLP with Hugging Face for text processing and chatbots.
Deploying AI models on cloud platforms like AWS or Azure.
Ethical AI practices and bias mitigation in AI systems.

Requirements

A laptop with Python 3.8+ installed (free download).
Basic knowledge of Python or programming (recommended, not mandatory).
Enthusiasm for AI and machine learning.

Machine Learning and AI Course Syllabus

Download Syllabus

Course Curriculum

Our Machine Learning and AI course in Pune offers a comprehensive curriculum, covering Python, Machine Learning, Deep Learning, Generative AI, NLP, ChatGPT, and MLOps. Designed for beginners and professionals, it includes hands-on projects to build a job-ready AI portfolio for Pune’s tech hub, targeting roles at companies like Infosys, TCS, and Wipro.

ML and AI Introduction
Applications of ML and AI

Basic Programming
NLP Libraries - Spacy & Gensim
OpenCV & Tensorflow, Keras

Sampling & Sampling Statistics
Inferential Stats: Hypothesis Testing
Derivatives
Optimization
Function, Scalar-Vector-Matrix, Vector Operation
Space, Probability, Distribution

Unsupervised K-Means & Hierarchical Clustering
Linear Regression
Logistic Regression
Train, Test & Validation Distribution
Gradient Descent
Decision Tree & KNN, Random Forest | Bagging & Boosting

Deep Learning Importance [Strength & Limitation]
SP | MLP
Neural Network Overview
Neural Network Representation
Activation Function, Loss Function
Importance of Non-linear Activation Function, Gradient Descent for Neural Network

Train, Test & Validation Set
Vanishing & Exploding Gradient
Dropout
Regularization
Bias Correction, RMS Prop, Adam, Ada, AdaBoost
Learning Rate, Tuning, Softmax

Introduction to Computer Vision, Image, Image Transformation, Filters, Noise Removal, Edge Detection, Non-Max Suppression, Hysteresis
Object Detection Concepts, Bounding Box, Object Detection Models, Landmark Detection, RCNN, Fast RCNN, Faster RCNN, Mask RCNN, YOLO Pre-trained Models, Transfer Learning, Segmentation Concepts
Advanced CNN Models Applications, Face Detection and Recognition, Different Techniques in Face Recognition, Style Transfer

Introduction, Automated Speech Recognition (ASR)
Text to Speech Conversion, Voice Assistant Devices, Building Alexa Skills

Basics of Autoencoders, Different Types of Autoencoders, Applications with Examples, Variational Autoencoders, Intro to Gen AI
GAN Basics and Foundations, Upsampling, GAN Models, Evaluate GAN Models, Inception Score, Frechet Inception Distance, GAN Loss Functions
Conditional GAN, Info GAN, Auxiliary GAN, Applications
Image Translation Applications, Cycle GAN Concepts and Implementations

Intro to RL, Q Learning, Exploration, Exploitation
Work with Deep RL Libraries, OpenAI Gym Library, Policy Gradient Concepts, Actor-Critic Methods, Proximal Policy Optimization (PPO) and Related Concepts

ARIMA, Deep Learning Models for Forecasting (RNN, LSTM, Transformer Applications)

Introduction to Text Mining, VSM, Word Embeddings Applications, RNN, GRU, LSTM Models, Intro to Transformers, Attention (Elmo, BERT, T5)
Word Clouds and Document Similarity using Cosine Similarity, Named Entity Recognition, Machine Translation using Hugging Face Libraries, Emotion Mining using Different Libraries, Web Scraping
Text Classification using Naïve Bayes, Frequentists vs Bayesian, Apriori, Posteriori Distributions, Bayesian Estimators: Posterior Mean, Posterior Median
Intro to Transformers & Attention (Single Head, Multi Head), Pretrained Models (GPT, BERT, BART, T5) Models with Applications, Examples using Python, Intro to Different Types of Transformer Encoder Models - Basic BERT, RoBERTa, DistilBERT, etc., Intro to Different Types of Transformer Decoder Models - GPT, GPT2, Other Variants of GPT, etc., GPT Progress, Calling OPENAI APIs, LLM Playgrounds, Intro to Different Types of Transformer Sequence to Sequence Models - BART, T5

Value Add Courses

Python Introduction - Programming Cycle of Python, Python IDE and Jupyter Notebook
Variables, Data Type
Create, Insert, Update and Delete Operation, Handling Errors
Operator - Arithmetic, Comparison, Assignment, Logical, Bitwise Operator, Decision Making - Loops
While Loop, For Loop and Nested Loop, Number Type Conversion - int(), long(), float(), Mathematical Functions, Random Function, Trigonometric Function
Strings - Escape Char, String Special Operator, String Formatting Operator, Built-in String Methods - center(), count(), decode(), encode()
Python List - Accessing Values in List, Delete List Elements, Indexing Slicing & Matrices, Built-in Function - cmp(), len(), min(), max(), List Comprehension
Tuples - Accessing Values in Tuples, Delete Tuples Elements, Indexing Slicing & Matrices, Built-in Tuples Functions - cmp(), len()
Dictionary - Accessing Values from Dictionary, Deleting and Updating Elements in Dict., Properties of Dict., Built-in Dict Functions & Methods, Dict Comprehension, Date & Time - Time Tuple, Calendar Module and Time Module
Function - Define Function, Calling Function, Pass by Reference as Value, Function Arguments, Anonymous Functions, Return Statements, Scope of Variables - Local & Global, Decorators and Recursion, Map Reduce and Filter
Import Statements, Locating Modules - Current Directory, Pythonpath, Dir() Function, Global and Location Functions and reload() Functions, Sys Module and Subprocess Module, Packages in Python
Files in Python - Reading Keyboard Input, Input Function, Opening and Closing Files, Syntax and List of Modes, Files Object Attribute - Open, Close, Reading and Writing Files, File Position, Renaming and Deleting Files, Pickle and Json
mkdir Method, chdir() Method, getcwd Method, rm dir
Exception Handling - List of Exceptions - Try and Exception, Try-Finally Clause and User-Defined Exceptions
OOP Concepts, Class, Objects, Inheritance, Overriding Methods like _init_, Overloading Operators, Data Hiding
Match Function, Search Function, Matching vs Searching, Regular Expression Modifiers and Patterns
Database Connectivity, Methods - MySQL, Oracle, How to Install MySQL, DB Connection, Create, Insert, Update and Delete Operation, Handling Errors
Introduction to Django Framework, Overview, Environment, Apps Life Cycle, Creating Views, Application, Rest API

What is ChatGPT?
The History of ChatGPT
Applications of ChatGPT
ChatGPT vs Other Chatbot Platforms
Industries Using ChatGPT
The Benefits and Limitations of ChatGPT
Future Developments in ChatGPT Technology
Ethical Considerations Related to ChatGPT and AI
Narrow AI, Strong AI, Superintelligence
ChatGPT Architecture
How Does ChatGPT Work?
ChatGPT Functionalities
Drafting Emails and Professional Communication
Automating Content Creation
Resume and Cover Letter Creation
Research and Information Gathering
Brainstorming Ideas and Creative Problem Solving
Best Practices for Using ChatGPT
What is Prompt Engineering?
Types of Prompts
Crafting Effective Prompts
Using ChatGPT to Generate Prompts

The Nature of AI, Comparison of Descriptive and Generative AI
Core Concepts in NLP, Basics of Language Understanding
Overview of LLMs, Their Scope, Capabilities, and Use Cases
What is GPT, Its Evolution, and Generational Changes
What is Prompt Engineering, Its Importance, Types of Prompts
Strategies for Generating Text, Video Scripts, and Music using Prompts
The Role and Understanding of Tokens, Introduction to Prompt Parameters
Deep Dive into Zero-Shot, One-Shot, and Few-Shot Learning
Introduction to Model Parameter Adjustments
Strategies for Managing AI Hallucinations and Biases
Methods for Crafting Complex Prompts, Incorporating Creativity and Context
Techniques for Prompt Refinement and Iterative Improvement
How to Assess Prompt Quality and Performance
Techniques for Collecting and Analyzing Human Feedback on Prompts
How to Assess Prompt Performance Across Different AI Models and Tasks

LLM, Use Cases, Text Generation, Chatbot Creation
Generative Adversarial Networks (GANs), Autoencoders in Generative AI
Significance of Transformers in AI, "Attention is All You Need" - Transformer Architecture
Reinforcement Learning, RLHF
Real-World Applications and Case Studies of LLMs
Instruction Fine-Tuning, Fine-Tuning on a Single Task, Multi-Task Instruction Fine-Tuning, Model Evaluation, Benchmarks, Parameter Efficient Fine-Tuning (PEFT), PEFT Techniques: LoRA, Soft Prompts, Lab 2 Walkthrough
Rouge1, BLEU, Meteor, CIDEr

What is MLOps, Different Stages in MLOps, ML Project Lifecycle, Job Roles in MLOps
What is Development Stage of an ML Workflow, Pipelines and Steps, Artifacts, Materializers, Parameters & Settings
Stacks & Components, Orchestrators, Artifact Stores, Flavors, etc.
ML Server Infrastructure, Server Deployment, Metadata Tracking, Collaborations, Dashboards

Our Trainers

Expert AI Trainers

Our trainers are AI experts with over 10 years of experience in machine learning, deep learning, and Python, having guided over 5,000 students to success in Pune’s tech industry.

12+ years of expertise in AI and machine learning technologies.
Trained 5,000+ students across Pune and Maharashtra.
Certified professionals with hands-on AI project experience.
Connected with HR teams at Infosys, TCS, and Wipro.
Updated with the latest AI frameworks and trends.

Career Benefits of Artificial Intelligence Training

Why Learn Artificial Intelligence?

Artificial Intelligence is transforming industries like healthcare, finance, and technology with applications in automation, predictive analytics, and NLP. Our course at Python Training Institute in Pune equips you with skills to excel in Pune’s AI-driven market, from startups to MNCs like TCS and Infosys.

With hands-on projects and placement support, you’ll build a portfolio that stands out, ensuring a rewarding AI career in just 90 days.

Key Benefits

High Demand: AI experts are sought by tech, healthcare, and finance sectors.
Lucrative Salaries: Earn ₹7L–₹30L annually in roles like AI Engineer.
Versatile Roles: Work as an AI Engineer, Data Scientist, or ML Researcher.
Global Opportunities: AI skills open doors to MNCs and startups worldwide.
Future-Proof: Stay relevant with AI’s growing applications in automation.

AI Job Roles and Salaries in Pune

Career Opportunities

Our Artificial Intelligence course prepares you for top AI roles in Pune’s IT hub. Below are key job profiles, responsibilities, and salary ranges for AI professionals in Pune.

Job Profile	Role Description	Average Salary (INR)
AI Engineer	Design and deploy AI models using machine learning and deep learning.	Entry-Level: ₹7L–₹12L Experienced: ₹15L–₹30L
Data Scientist	Analyze data and build predictive models with AI frameworks.	Entry-Level: ₹6L–₹10L Experienced: ₹12L–₹22L
Machine Learning Engineer	Create machine learning models using TensorFlow and PyTorch.	Entry-Level: ₹7L–₹11L Experienced: ₹15L–₹28L
AI Researcher	Explore innovative AI solutions for real-world applications.	Entry-Level: ₹8L–₹13L Experienced: ₹18L–₹35L
AI Consultant	Advise companies on implementing AI solutions.	Entry-Level: ₹6L–₹10L Experienced: ₹12L–₹25L

Key Notes

Salaries vary based on experience, company, and project complexity.
Pune’s IT hub offers competitive pay for AI professionals.
Certifications enhance earning potential and job prospects.

Why Choose Our AI Training in Pune?

Your Path to Success

Python Training Institute in Pune offers a transformative AI learning experience, equipping you with skills to excel in AI-driven industries. Our course is tailored for Pune’s tech market, ensuring you stand out to employers like TCS, Wipro, and Infosys.

With a focus on practical training and career support, we help you achieve your AI goals in just 90 days, backed by our Kharadi-based facility and expert instructors.

Why Us?

Expert Instructors: Learn from AI professionals with 12+ years of expertise.
Hands-On Projects: Build AI models like predictive systems and chatbots.
Placement Support: 100% assistance with resume building and interviews.
Flexible Learning: Online and classroom options for Pune and Maharashtra learners.
Industry Certification: Earn a credential recognized by Pune’s top employers.

AI Training Modes in Pune

Flexible Learning Paths

Our Artificial Intelligence course offers multiple training modes to suit your needs, whether you’re a student in Kharadi or a professional in Mumbai. Learn at our state-of-the-art facility in Pune or join live online sessions from anywhere in Maharashtra.

Each mode includes hands-on AI projects and placement support, ensuring you’re ready for Pune’s competitive AI job market.

Training Modes

Classroom Training: In-person classes at our Kharadi, Pune center for hands-on learning.
Online Training: Live, interactive sessions for learners in Pune, Mumbai, and beyond.
Corporate Training: Tailored AI programs for teams in Pune’s IT companies.