Overview of Course

Our Artificial Intelligence Training course is designed to provide a comprehensive understanding of AI concepts, tools, and techniques. It covers topics such as Machine Learning, Deep Learning, Natural Language Processing, and Robotics, among others. This course is perfect for individuals who want to learn about the latest trends and developments in the field of Artificial Intelligence.

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Course Highlights

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Hands-on training on the latest AI tools and technologies

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Real-world examples and case studies

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Experienced trainers with industry experience

Key Differentiators

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    Personalized Learning with Custom Curriculum

    Training curriculum to meet the unique needs of each individual

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    Trusted by over 100+ Fortune 500 Companies

    We help organizations deliver right outcomes by training talent

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    Flexible Schedule & Delivery

    Choose between virtual/offline with Weekend options

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    World Class Learning Infrastructure

    Our learning platform provides leading virtual training labs & instances

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    Enterprise Grade Data Protection

    Security & privacy are an integral part of our training ethos

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    Real-world Projects

    We work with experts to curate real business scenarios as training projects

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Skills You’ll Learn


Machine Learning techniques


Deep Learning concepts


Natural Language Processing (NLP)


Robotics and automation


Neural Networks


Python programming


AI model deployment

Training Options

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1-on-1 Training

On Request
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

On Request
  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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Course Reviews


  • Introduction to Artificial Intelligence and Machine Learning
  • Evolution of AI and ML
  • Types of AI: Reactive, Limited Memory, Theory of Mind, Self-Aware
  • Types of ML: Supervised, Unsupervised, Semi-Supervised, Reinforcement
  • Applications of AI and ML in various industries
  • Ethics and Responsible AI

  • Introduction to Python programming language
  • Variables, Data Types, and Operators
  • Conditional Statements and Loops
  • Functions and Modules
  • Object-Oriented Programming
  • File Handling

  • Numpy: Numerical computing in Python
  • Pandas: Data manipulation and analysis
  • Matplotlib: Data visualization
  • Scikit-learn: Machine learning library
  • Keras and TensorFlow: Deep learning libraries
  • Natural Language Toolkit (NLTK): Natural Language Processing (NLP) library

  • Introduction to Data Management
  • Data Acquisition and Cleaning
  • Data Storage and Retrieval
  • Data Warehousing and Mining
  • Big Data and Hadoop
  • Data Visualization and Reporting

  • Introduction to SAS
  • Data Preparation and Exploration
  • Data Analysis and Reporting
  • Advanced SAS Techniques
  • SAS Macros and Functions
  • SAS Certification

  • Introduction to Statistics
  • Descriptive Statistics
  • Inferential Statistics
  • Probability Theory
  • Hypothesis Testing
  • Regression Analysis

  • Introduction to Predictive Analytics
  • Data Preprocessing and Feature Selection
  • Regression Analysis for Prediction
  • Classification Techniques for Prediction
  • Time Series Analysis for Prediction
  • Model Selection and Evaluation

  • Introduction to Machine Learning
  • Supervised Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines (SVM)
  • Unsupervised Learning: K-Means Clustering, Hierarchical Clustering, Principal Component Analysis (PCA)
  • Model Selection and Evaluation

  • Introduction to Artificial Intelligence
  • Search Algorithms: Breadth-First Search, Depth-First Search, A* Search
  • Game Playing: Minimax Algorithm, Alpha-Beta Pruning
  • Knowledge Representation and Reasoning
  • Natural Language Processing
  • Computer Vision

  • Introduction to Deep Learning
  • Artificial Neural Networks
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Autoencoders
  • Transfer Learning

  • Advanced CNN Architectures: VGG, ResNet, Inception, Xception
  • Generative Adversarial Networks (GANs)
  • Object Detection and Recognition
  • Image Segmentation
  • Natural Language Generation
  • Reinforcement Learning

  • Introduction to Cloud Computing
  • AWS Fundamentals
  • Compute Services: EC2, Lambda, Elastic Beanstalk
  • Storage Services: S3, EBS, Glacier
  • Database Services: RDS, DynamoDB
  • Networking Services: VPC, Route 53, CloudFront

  • Introduction to Tableau
  • Data Connections and Preparation
  • Data Visualization with Tableau
  • Calculations and Expressions
  • Dashboards and Stories
  • Advanced Tableau Features
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Target Audience:

  • Students and graduates looking to start a career in AI
  • Professionals looking to upskill in AI and related technologies
  • Entrepreneurs interested in implementing AI in their businesses
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  • Basic programming knowledge
  • Familiarity with mathematics and statistics
  • Basic knowledge of linear algebra and calculus
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Benefits of the course:

  • Learn from experienced trainers with industry experience
  • Hands-on training on the latest AI tools and technologies
  • Real-world examples and case studies
  • Industry-recognized certification
  • Access to a community of AI professionals
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Exam details to pass the course:

  • There will be a final exam at the end of the course.
  • The passing score for the exam is 70%.
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Certification path:

  • Certification in Artificial Intelligence (CAI)
  • Certification in Machine Learning (CML)
  • Certification in Deep Learning (CDL)
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Career options:

  • AI Developer
  • Machine Learning Engineer
  • Data Scientist
  • AI Researcher
  • Robotics Engineer

Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Experienced trainers with industry experience
  • Bullet Icon Hands-on training on the latest AI tools and technologies
  • Bullet Icon Real-world examples and case studies
  • Bullet Icon Industry-recognized certification
  • Bullet Icon Access to a community of AI professionals
  • Bullet Icon Flexible learning options


Basic programming knowledge, familiarity with mathematics and statistics, and basic knowledge of linear algebra and calculus.

The course duration is 60 hours.

The passing score for the exam is 70%.

Yes, this course is suitable for beginners who have a basic understanding of programming, mathematics, and statistics.

Yes, you can access the course material even after completing the course.

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