MODULES INCLUDED

  • What is Artificial Intelligence?
    • History of Artificial Intelligence
    • Need of Artificial Intelligence
    • State of Art
    • The Turing Test
  • Intelligent Agents
    • Agents and Environment
    • Structure of Agents
  • Searching
    • Uninformed search
    • Informed search
    • Brute force search
    • Adversarial Search
    • Constraint satisfaction problems
  • Logic
    • Propositional Logic
    • Predicate Logic
    • Deduction
  • First Order Logic
  • Planning
  • Knowledge Representation
  • Rule Based System
  • Basic Probability Concepts
  • Bayesian Inference
  • Naive Bayes Models
  • Bayesian Networks
  • Markov Model
  • Hidden Markov Model
  • Association rules
  • Dimensionality reduction
  • Feature selection and visualization
  • What is Machine Learning?
  • Types of Learning
    • Supervised learning
    • Unsupervised Learning
    • Semi-Supervised Learning
  • Decision Tree
  • Clustering and Classification
  • Regression
  • Support Vector Machine
  • What is Reinforcement learning
  • Passive Reinforcement learning
  • Active Reinforcement learning
  • Searching in Reinforcement learning
  • Applications of Reinforcement learning
  • Natural Language Processing
    • Language Models
    • Information Retrieval
    • Information Extraction
  • Natural Language Processing for Communication
    • Syntactic Analysis
    • Augmented Grammar and Semantic Analysis
    • Machine Translation
    • Speech Recognition
  • Perception
    • Image Formation
    • Image Processing Operation
      • Edge Detection
      • Segmentation
      • Finding Depth
      • Finding Orientation
      • Object Recognition
  • What is a Neural Network?
  • Neural Network Representation
  • Types of Neural Network
    • Single Layer Network
    • Multi-Layer Network
  • Feedforward Neural Network
  • Convolutional Neural Network
  • Recurrent Neural Network
  • Neural Network Learning- Backpropagation
  • Healthcare
  • Robotics
  • Entertainment
  • There will be an online training followed by a multiple choice exam of 100 marks.
  • You need to acquire 60+ marks to clear the exam.
  • If you fail, you can retake the exam after one day.
  • You can take the exam no more than 3 times.
  • If you fail to acquire 60+ marks even after three attempts, then you need to contact us to get assistance for clearing the exam

Certification Benefits

  • Provides a validation for your skills improving career opportunities
  • Improved potential for a higher salary
  • A secure digital certification for expanding your knowledge base

What you get?

  • Global Tech Council Certification
  • Career guidance in big data analytics domain
  • Peer-to-Peer networking opportunity
  • 1 to 1 counselling with our career experts

CAREER FACTS

Top job functions

  • Finance
  • Retail
  • Information Technology
  • Operations
  • Sales
  • Manufacturers


What does a Artificial Intelligence Expert do?

An artificial intelligence expert is required in a variety of settings including private companies and public organizations in multiple positions.

The Growth Curve ahead:

  • Analytics Director
  • Artificial Scientist
  • Machine Learning Engineer
  • Data scientist
  • Data Engineer

Final Outcome

After completing this certification, you would have mastered the core concepts of Artificial Intelligence.

Instructor Profile

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