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Artificial Intelligence 18 - 24 Week Certification Course

Learn From Industry Experts

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* No Prior Coding Experience Required

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KEY FEATURES

Live Classes

18 - 24 Weeks

Lab Support

For Practicals

Industry Expert

Learn From Top Industry Expert

Live Projects

Work On Capstone Projects

Overview of this Certification Course

This Artificial Intelligence course is a comprehensive and forward-looking program designed to provide students with a deep understanding of artificial intelligence, its applications, and its transformative potential across various industries. This course offers a holistic view of AI, covering both foundational concepts and advanced topics, making it suitable for individuals with varying levels of AI expertise.

Prerequisites of this Course

Course objectives

Who can apply?

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Skills You Learn From this Course

Fundamental AI Concepts

Machine Learning Skills

Deep Learning and Neural Networks

Natural Language Processing (NLP)

Computer Vision

And Many More...

Course Curriculum

Chapter 1 Introduction to Artificial Intelligence:

  • Historical perspective and evolution of AI.
  • Key terminologies and definitions. ‘
  • The AI problem-solving approach.

Chapter 2 Machine Learning Foundations:

  • Supervised, unsupervised, and reinforcement learning.
  • Feature engineering and model selection.
  • Evaluation and validation of machine learning models.

Chapter 3 Deep Learning and Neural Networks:

  • Neural network architecture and training.
  • Convolutional Neural Networks (CNN) for image analysis.
  • Recurrent Neural Networks (RNN) for sequential data.

Chapter 4 Natural Language Processing (NLP):

  • Text preprocessing and tokenization.
  • Sentiment analysis.
  • Language modeling and machine translation.

Chapter 5 Computer Vision:

  • Image preprocessing and feature extraction.
  • Object detection and image classification.
  • Image segmentation and face recognition.

Chapter 6 Robotics and Autonomous Systems:

  • Introduction to robotics and control systems.
  • Path planning and navigation.
  • Human-robot interaction and AI in robotics.

Chapter 7 Ethical and Societal Implications:

  • Discussion on AI ethics and responsible AI.
  • Bias and fairness in AI algorithms.
  • Privacy and security concerns in AI. 

Chapter 8 AI Applications in Industry:

  • Real-world case studies showcasing AI applications in healthcare, finance, autonomous vehicles, and more.
  • Guest lectures from industry experts.

Chapter 9 AI Project Development:

  • Students will engage in hands-on AI projects, applying their knowledge to solve practical problems.
  • Project topics may range from developing AI chatbots to creating image recognition systems.

  • Exploration of cutting-edge AI technologies such as reinforcement learning, generative adversarial networks (GANs), and quantum AI.

Chapter 11 . Capstone Project:

  • In the final stage of the course, students will work on a capstone project, demonstrating their proficiency in AI by tackling a complex real-world problem.

Continuous Assessment:

  • Continuous assessment through quizzes, assignments, and project submissions. Final examination. Evaluation of the capstone project.

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*Initial one-to-one consultation, Health & Fitness Assasments Bespoke training program planing, Custom Nutrition plan & recipes. Weekly Progress Reviews

*Initial one-to-one consultation, Health & Fitness Assasments Bespoke training program planing, Custom Nutrition plan & recipes. Weekly Progress Reviews

*Initial one-to-one consultation, Health & Fitness Assasments Bespoke training program planing, Custom Nutrition plan & recipes. Weekly Progress Reviews

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