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DiplomaX Online Learning Institute

Artificial Intelligence (AI) Course

About Course

The Artificial Intelligence (AI) Course is a comprehensive, beginner-to-advanced training program designed to help you understand the foundations of Artificial Intelligence and learn how intelligent systems are built and applied in the real world. As AI continues to transform industries such as healthcare, finance, education, marketing, cybersecurity, and software development, this course equips you with the practical skills needed to thrive in the AI-driven future.

Starting with the fundamentals, you will learn what Artificial Intelligence is, how it works, and the different branches of AI, including Machine Learning, Deep Learning, Natural Language Processing (NLP), and Computer Vision. You will also explore how modern AI models are trained, how they make predictions, and how businesses use AI to automate tasks and improve decision-making.

Throughout the course, you will gain hands-on experience using Python and industry-leading AI libraries to build intelligent applications. You will learn data preprocessing, model training, model evaluation, prompt engineering, AI automation, and how to work with generative AI tools. In addition, you will explore ethical AI development, responsible AI practices, and the limitations of current AI technologies.

The course includes real-world projects that allow you to build AI-powered chatbots, recommendation systems, image classifiers, text analysis applications, predictive models, and intelligent automation solutions. By the end of the course, you will have the confidence to design, develop, and deploy AI applications for personal projects, businesses, or professional careers.

Whether your goal is to become an AI Engineer, Machine Learning Developer, Data Scientist, Automation Specialist, or simply understand the future of Artificial Intelligence, this course provides the knowledge, practical experience, and industry-ready skills needed for success.

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What Will You Learn?

  • Understand the fundamentals of Artificial Intelligence
  • Learn the history and evolution of AI
  • Explore different branches of AI
  • Master Python programming for AI development
  • Learn Machine Learning fundamentals
  • Understand Deep Learning concepts
  • Build neural network models
  • Learn Natural Language Processing (NLP)
  • Explore Computer Vision applications
  • Work with Generative AI tools
  • Create AI-powered chatbots and virtual assistants
  • Learn prompt engineering techniques
  • Build predictive AI models
  • Prepare and preprocess datasets
  • Train, test, and evaluate AI models
  • Understand model optimization techniques
  • Learn AI automation workflows
  • Build real-world AI projects
  • Understand AI ethics, privacy, and responsible AI
  • Create a professional AI portfolio

Course Content

Artificial Intelligence

  • Introduction to Artificial Intelligence
    12:00
  • History and Evolution of AI
    08:40
  • Types of Artificial Intelligence
    02:29
  • AI Applications in the Real World
    01:21
  • AI vs Machine Learning vs Deep Learning
    06:06
  • Setting Up the AI Development Environment
    06:35
  • Python Basics for AI
    06:37
  • Data Collection and Preparation
    16:18
  • Data Preprocessing Techniques
    05:00
  • Introduction to Machine Learning
    06:50
  • Supervised Learning
    09:01
  • Unsupervised Learning
    13:23
  • Reinforcement Learning Basics
    03:42
  • Feature Engineering Fundamentals
    15:11
  • Linear Regression
    04:01
  • Logistic Regression
    09:12
  • Decision Trees
    05:19
  • Random Forest Algorithm
    07:00
  • Support Vector Machines (SVM)
    04:17
  • K-Means Clustering
    05:14
  • Model Training and Evaluation
    09:15
  • Overfitting and Underfitting
    01:22
  • Neural Networks Fundamentals
    01:44
  • Deep Learning Introduction
    06:16
  • Introduction to TensorFlow and Keras
    20:00
  • Natural Language Processing (NLP) Basics
    15:28
  • Computer Vision Fundamentals
    02:00
  • AI Chatbots and Virtual Assistants
    04:55
  • Generative AI and Large Language Models (LLMs)
    03:48
  • Prompt Engineering Techniques
    14:24
  • Deploying AI Models to Production
    07:52

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