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Course Highlights

Comprehensive Introduction to AI & ML

Build a strong foundation in Artificial Intelligence (AI) and Machine Learning (ML) concepts, applications, and industry use cases.

AWS AI Services & Tools

Learn how to leverage AWS AI/ML services such as Amazon SageMaker, AWS DeepLens, Amazon Polly, Amazon Rekognition, and Amazon Lex to build intelligent applications.

Industry-Aligned Pathway

Content curated by AWS experts, aligned with in-demand industry roles, to equip learners with applied skills in AI/ML for cloud-driven organizations.

Modular Learning Path Covers Foundational to Practitioner-level Content Across:

  • AI fundamentals & ethics
  • Machine Learning basics
  • Computer vision, speech, and language AI services
  • Building, training, and deploying ML models using AWS tools
  • Workforce Readiness
  • Designed to help learners, early career professionals, and working practitioners adopt AI skills to stay competitive in the evolving digital economy

  • Skill Type

  • Course Duration

  • Domain

  • GOI Incentive applicable

  • Course Category

  • Nasscom Assessment

  • Placement Assistance

  • Certificate Earned

  • Badge Earned

  • Content Alignment Type

  • NOS Details

  • Mode of Delivery

Course Details

Learning Objectives

By the end of this Learning Plan, learners will be able to:

Foundations of AI & ML

  • Explain the fundamental concepts of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning
  • Differentiate between supervised, unsupervised, and reinforcement learning approaches
  • Identify real-world applications and use cases of AI across industries

      • AWS AI/ML Services Overview

      • Understand the AWS AI/ML service portfolio and it's capabilities (Amazon SageMaker, AWS Lex, AWS Polly, AWS Rekognition, AWS Comprehend, etc.)
      • Explore how AWS cloud services integrate AI into scalable business solutions

      Model Development Lifecycle

      • Describe the typical steps in building, training, and deploying ML models
      • Recognize the importance of data collection, preparation, and feature engineering in AI
      • Understand ethical considerations and responsible AI practices

      Hands-on Exploration

      • Navigate and use key AWS AI services for text, speech, vision, and language understanding
      • Demonstrate basic workflows using Amazon SageMaker for building and deploying ML models
      • Use AWS AI tools to solve sample business problems

      AI for Business & Decision-making

      • Understand how AI can drive innovation, automation, and data-driven decision-making
      • Identify opportunities to integrate AI in workplace scenarios
      • Communicate AI concepts effectively to both technical and non-technical stakeholders

      Readiness for Next Steps

      • Prepare for advanced AI/ML learning pathways and certifications on AWS
      • Gain confidence in leveraging AWS AI services for projects, solutions, and organizational needs
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Reasons to enrol
  • Industry-relevant Curriculum - Learn the foundations of Artificial Intelligence (AI) and Machine Learning (ML) with AWS, the world’s leading cloud services provider
  • Future-ready Skills - Gain practical knowledge of AI concepts, services, and applications to stay ahead in a rapidly evolving digital economy
  • Hands-on Learning - Explore AWS AI/ML services through real-world scenarios and guided learning resources designed for beginners and practitioners alike
  • Career Advancement - Build capabilities that are highly valued by employers across industries, boosting your employability and career growth
  • Flexible & Self-paced - Learn anytime, anywhere at your own pace. Ideal for working professionals and students
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Ideal Participants

This learning plan is designed for:

  • Students and Early Career Professionals - Individuals from technical and non-technical backgrounds looking to build foundational to intermediate knowledge in Artificial Intelligence (AI) and Machine Learning (ML)
  • IT Professionals and Developers - Practitioners seeking to understand how to apply AI/ML concepts using AWS services and integrate them into real-world projects
  • Data Analysts and Engineers- Professionals aspiring to enhance their data-driven decision-making by leveraging AI-powered solutions
  • Educators and Trainers - Faculty members and institutional trainers aiming to incorporate AI fundamentals and AWS AI tools into their teaching curriculum
  • Business and Functional Leaders- Managers and decision-makers who want to gain awareness of AI applications to drive innovation, improve processes, and strengthen digital strategies

    • This plan caters to participants with basic digital fluency; prior coding or cloud experience is beneficial but not mandatory.

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Curriculum

Curriculum

  • Understand core AI/ML concepts and terminology
  • Explore AWS AI/ML services such as Amazon SageMaker, AWS Rekognition, Comprehend, Polly, Lex, and Transcribe
  • Apply machine learning workflows for training, testing, and deployment
  • Build AI-enabled applications
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skills and tools

Skills Covered

  • Artificial Intelligence Fundamentals
  • Introduction to AI concepts, applications, and industry relevance
  • Understanding AI ethics and responsible AI practices
  • Machine Learning Foundations
  • Core ML concepts: supervised, unsupervised, and reinforcement learning
  • Data preprocessing, model training, testing, and evaluation
  • Deep Learning Essentials
  • Neural networks, activation functions, and optimization techniques
  • Building and training deep learning models
  • Natural Language Processing (NLP)
  • Text analysis, sentiment detection, and conversational AI basics
  • Using AWS services for NLP applications
  • Computer Vision
  • Image classification and object detection fundamentals
  • Applying AWS AI/ML tools for vision-based use cases
  • AI Deployment & Integration
  • Using AWS cloud services to deploy AI models
  • API integration and model serving for applications

Tools & Platforms

  • AWS AI/ML Services
  • Amazon SageMaker – model building, training, and deployment
  • AWS DeepLens – deep learning-enabled video camera for developers
  • Amazon Polly – text-to-speech service
  • Amazon Lex – conversational AI and chatbot development
  • Amazon Rekognition – image and video analysis
  • Amazon Comprehend – NLP and sentiment analysis
  • Programming & Frameworks
  • Python for AI/ML development
  • TensorFlow & PyTorch basics within AWS environment
  • Cloud Integration
  • AWS Management Console & CLI
  • Cloud-native AI model deployment practices
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