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Artificial Intelligence Training
Master AI concepts, Machine Learning, Deep Learning, NLP, Generative AI, and real-world applications through hands-on projects and expert-led training.
Hands-on AI projects with industry-oriented training
Hands-on AI projects with industry-oriented training
Live Training
Instructor-led Online Training
Interactive live classes with expert trainers, practical learning,
LMS access, and cloud labs.
Live mentor sessions
Dedicated lab access
Weekend batches
Most popular
Self Paced
Recorded Video Training
Learn anytime with premium recorded sessions, downloadable study materials, and flexible access.
Unlimited recordings
LMS access included
Flexible learning
Flexible Access
Enterprise
Corporate Training
Team-oriented learning solutions with LMS integration, reporting, and enterprise support.
Team learning
Progress tracking
Dedicated support
Business Ready
Kasha Training
About The Course
AI (Artificial Intelligence) is a branch of computer science that focuses on creating systems capable of performing tasks that would normally require human-level intelligence. This includes things like understanding natural language, recognizing patterns, making decisions, and learning from experience. AI is a wide discipline with numerous subfields, each with unique objectives and specializations.
Artificial intelligence refers to technology that can analyze information, recognize patterns, generate content, and help complete tasks that typically require human judgment. AI is used across industries for tasks such as research, data analysis, writing, coding, and automation — which is why millions of professionals are actively learning to use it effectively.
AI is the principle of simulating human intelligence with computers programmed to emulate human thought patterns and mimic their actions. Technology in this field grows day by day — steering use into the future by predicting situations and helping to solve complex problems. Real-world examples include wayfinding apps, fraud detection systems in financial institutions, retail inventory management, robot vacuums, self-driving cars, and chess-playing computers.
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Benefits of Attending Artificial Intelligence Training
- Gain industry-recognized Artificial Intelligence skills highly sought after across Technology, Healthcare, Finance, Retail, Manufacturing, and Automotive sectors
- Opens career opportunities as an AI Engineer, Machine Learning Engineer, Data Scientist, AI Research Scientist, NLP Engineer, and Computer Vision Engineer
- Learn the most transformative and fastest-growing technology of the 21st century powering innovations across every industry globally
- Boost your earning potential — AI professionals are among the highest-paid technology specialists commanding premium salaries worldwide
- Develop strong skills in designing, building, and deploying intelligent systems that can learn, reason, and make decisions autonomously
- Ability to work on cutting-edge real-world AI applications including Chatbots, Recommendation Systems, Fraud Detection, Image Recognition, and Autonomous Vehicles
- Master key AI technologies and frameworks — TensorFlow, PyTorch, Scikit-learn, Keras, OpenCV, and Hugging Face Transformers
- Prepares you for globally recognized AI certifications such as Google Professional Machine Learning Engineer, IBM AI Engineering Professional, and Microsoft Certified Azure AI Engineer
- Enhances analytical thinking, mathematical reasoning, and problem-solving skills essential for developing intelligent AI-powered solutions
- Builds a strong foundation for advancing into Deep Learning, Natural Language Processing, Computer Vision, Generative AI, and Large Language Models (LLMs)
- Enables professionals to leverage AI tools and techniques to automate business processes and drive digital transformation initiatives
- Positions you at the forefront of technological innovation with skills applicable across virtually every industry and business domain
Key Features of Artificial Intelligence (AI) Training
- Comprehensive curriculum covering AI fundamentals to advanced intelligent system design and deployment concepts
- Hands-on, practical training with real-time projects, case studies, and live AI model development and deployment exercises
- Coverage of core AI topics: History of AI, Types of AI, Intelligent Agents, Problem Solving, Search Algorithms, and Knowledge Representation
- In-depth training on Machine Learning — Supervised Learning, Unsupervised Learning, Reinforcement Learning, and Semi-supervised Learning techniques
- Modules on key Machine Learning Algorithms — Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, K-Means, and KNN
- Training on Deep Learning — Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and LSTM Networks
- Coverage of Natural Language Processing (NLP) — Text Preprocessing, Tokenization, Sentiment Analysis, Named Entity Recognition, and Language Models
- Modules on Computer Vision — Image Classification, Object Detection, Image Segmentation, and Facial Recognition using OpenCV and Deep Learning
- Training on Generative AI — Large Language Models (LLMs), Prompt Engineering, GPT Architecture, and AI content generation techniques
- Coverage of Reinforcement Learning — Q-Learning, Deep Q-Networks (DQN), Policy Gradient Methods, and Reward Optimization strategies
- Modules on AI Model Deployment — REST APIs, Flask, FastAPI, Docker, and Cloud Deployment on AWS, Azure, and Google Cloud Platform
- Training on AI Ethics, Responsible AI, Bias Detection, Explainability (XAI), and Governance frameworks for enterprise AI solutions
- Coverage of AI tools and platforms — TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face, LangChain, and OpenAI APIs
- Modules on Feature Engineering, Hyperparameter Tuning, Model Evaluation, Cross Validation, and ML Pipeline Automation
- Live interactive sessions with certified AI professionals and experienced industry trainers
- Flexible learning modes — Online, Offline, and Self-paced options available
- Regular assignments, quizzes, mock interviews, and assessments to track learning progress
- Interview preparation support, resume building, and job placement assistance
- Industry-recognized course completion certificate upon successful training
- Dedicated student support and doubt-clearing sessions throughout the course
Our Programs
Course Curriculum
1. Introduction to Artificial Intelligence
Understand the fundamentals of Artificial Intelligence, its types, applications, intelligent systems, and real-world use cases. Learn how AI enables machines to think, learn, solve problems, and make intelligent decisions.
Fundamentals and history of AI
Video · 0:00 - 25:00
AI applications and real-world use cases
Video · Starts at 1:40
Lab:AI ethics and future trends
Reading 15 min
2.Python Programming for AI
Learn Python programming fundamentals, data structures, functions, OOP concepts, and essential libraries like NumPy, Pandas, and Matplotlib for AI development and data analysis.
Python basics and Advance concepts
Video · 5 min
Object- Oriented Programming(OOP) in Python
Video · 5 min
Lab: Data Manipulation with Numpy, Pandas and MatPlotlib
Lab 60 min
3.Machine Learning
Learn Python programming fundamentals, data structures, functions, OOP concepts, and essential libraries like NumPy, Pandas, and Matplotlib for AI development and data analysis.
Introduction to Machine Learning Concepts
Video · 5 min
Lab: Model trainrning, learning and Evaluation
Video · 5 min
4.Deep Learning & Neural Networks
Dive into neural network architecture and deep learning frameworks. Build, train, and tune multi-layer networks, and apply convolutional layers to solve real-world pattern recognition problems..
Neural Networks Fundamentals
Video · 5 min
Building Networks with TensorFlow & Keras and
Video · 5 min
Lab: Training a Convolutional Neural Network
Lab 75 min
5.Natural Language Processing
Explore how machines understand and generate human language. Cover text preprocessing, embeddings, transformer architectures, and hands-on text classification tasks.
NLP fundamentals & text processing
Video · 5 min
Language models & the Transformer architecture
Video · 5 min
Lab:Sentiment analysis & text classification
Project 120 min
6.Computer Vision
Teach machines to interpret visual data. Cover image processing, feature extraction, object detection, and image classification using modern CV libraries.
Image Processing with OpenCV
Video · 5 min
Object detection & image classification
Video · 5 min
Lab:Building an image recognization pipeline
Project 120 min
7. Generative AI & Large Language Models
Explore how generative models create text, images, and code. Learn prompt engineering, fine-tuning strategies, and how to integrate LLM APIs into real applications.
Introduction to Generative AI & LLMs
Video · 5 min
Prompt engineering & fine-tuning techniques
Video · 5 min
Lab: Building an AI chatbot with LLM APIs
Project 120 min
8.MLOps & Capstone Project
Bring it all together. Learn to deploy and scale models in production, monitor performance, and ship a complete end-to-end AI solution as your capstone project.
Model deployment & MLOPS fundamentals
Video · 5 min
Cloud AI services & scalling models
Video · 5 min
Project:-End-to-End AI solution Development
Video · 5 min
Lab: Deploying a machine AI Solution Development
Project 120 min
12
Modules
76
Lessons
42h
Total Duration
14
Coding Labs
4
Projects
Our Programs
Feedback from our Participants
Building supervised learning pipelines and tuning hyperparameters across regression and classification models gave me the hands-on mastery I needed to pass my interviews.
Arjun Rao
Artificial Intelligence (AI) is a branch of computer science that enables machines to perform tasks that normally require human intelligence, such as learning, reasoning, problem-solving, and decision-making.
The main types of AI are:
- Narrow AI
- General AI
- Super AI
AI is used in virtual assistants, healthcare, finance, education, robotics, self-driving cars, recommendation systems, and customer support.
Machine Learning (ML) is a subset of AI that enables computers to learn from data and improve their performance without being explicitly programmed.
Artificial Intelligence is the broader concept of making machines intelligent, while Machine Learning is a subset of AI that enables systems to learn from data automatically.
AI is the overall field of intelligent systems, while Deep Learning is a subset of Machine Learning that uses neural networks to solve complex problems.
AI systems require large amounts of quality data to learn patterns, make accurate predictions, and improve their performance over time.
Neural Networks are AI models inspired by the human brain. They process data through interconnected layers to recognize patterns and make predictions.
Artificial Intelligence (AI) is a branch of computer science that enables machines to perform tasks that normally require human intelligence, such as learning, reasoning, problem-solving, and decision-making.
The main types of AI are:
- Narrow AI
- General AI
- Super AI
AI is used in virtual assistants, healthcare, finance, education, robotics, self-driving cars, recommendation systems, and customer support.
Machine Learning (ML) is a subset of AI that enables computers to learn from data and improve their performance without being explicitly programmed.
Artificial Intelligence is the broader concept of making machines intelligent, while Machine Learning is a subset of AI that enables systems to learn from data automatically.
AI is the overall field of intelligent systems, while Deep Learning is a subset of Machine Learning that uses neural networks to solve complex problems.
AI systems require large amounts of quality data to learn patterns, make accurate predictions, and improve their performance over time.
Neural Networks are AI models inspired by the human brain. They process data through interconnected layers to recognize patterns and make predictions.
Our Programs