Artificial Intelligence

Overview

This training is designed to equip learners with a deep understanding of Artificial Intelligence concepts, tools, and practical applications. It covers everything from foundational theories to building and deploying AI-powered solutions using real-world datasets.

Request for Enrollment

Who Should Join?

  • Graduates and professionals in IT, math, or engineering
  • Data analysts, developers, or anyone interested in AI
  • Entrepreneurs exploring AI-based products

Need Assistance?

Email Us

training@intelliasofpro.com

Overall Outline

Artificial Intelligence (AI) focuses on creating systems that can simulate human intelligence and decision-making. It covers key concepts like machine learning, deep learning, natural language processing, and computer vision. Learners explore algorithms for classification, regression, clustering, and neural networks. The curriculum includes tools like Python, TensorFlow, and scikit-learn. Real-world applications in healthcare, finance, robotics, and automation are emphasized. Projects and case studies help build practical experience and problem-solving skills in AI.

Core Features

Introduction to AI

What is Artificial Intelligence / History, types (Narrow AI, General AI), and applications / AI vs Machine Learning vs Deep Learning

Mathematics for AI

Linear Algebra essentials / Probability and Statistics / Calculus basics for optimization

Python for AI

Python basics & packages / NumPy, Pandas, Matplotlib / Data preprocessing & visualization

Machine Learning

Supervised, Unsupervised & Reinforcement Learning / Algorithms: Linear Regression, Decision Trees, SVM, KNN / Model evaluation & tuning / Scikit-learn hands-on projects

Deep Learning

Introduction to Neural Networks / Activation Functions, Backpropagation / Convolutional Neural Networks (CNNs) / Recurrent Neural Networks (RNNs) / Frameworks: TensorFlow & Keras

Natural Language Processing (NLP)

Text processing & cleaning / Sentiment analysis / Chatbots & language models / Hugging Face Transformers (intro)

AI in Real-world Applications

Image and speech recognition / Recommendation systems / AI in healthcare, finance, and automation

Capstone Project

End-to-end AI project: data preparation, model training, evaluation, and deployment / Examples: Stock price prediction, image classification, chatbot, etc.

Hands-On Features

01

Real-world datasets and case studies

Hands-on experience with real-world datasets and case studies to apply AI concepts in practical, industry-relevant scenarios.

02

Live coding & project sessions

Live coding and project sessions to build, train, and deploy AI models using real-world techniques and tools.

03

Resume, LinkedIn & interview preparation

Comprehensive resume building and interview preparation focused on AI roles and industry expectations.