AWS Certified AI Course

The Goals

The course aims to:

• Build a clear understanding of artificial intelligence fundamentals.
• Learn the concepts of machine learning and its applications.
• Understand generative AI and its practical use cases.
• Differentiate between various types of AI technologies.
• Explore AI use cases within organizations.
• Understand how to select suitable solutions based on business requirements.
• Learn about AWS services related to artificial intelligence.
• Develop skills in using generative AI tools effectively.
• Understand responsible and ethical AI usage principles.
• Learn the fundamentals of AI security and privacy.
• Prepare for the AWS Certified AI Practitioner certification.
• Support professional development in technology and digital transformation fields.

Target Auidence

The AWS Certified AI Practitioner course is suitable for:

• Beginners interested in entering the field of artificial intelligence.
• Students and graduates from technical and non-technical backgrounds.
• Business analysts.
• Entry-level data analysts.
• Product managers.
• Project managers.
• Marketing and sales professionals.
• Digital transformation specialists.
• IT employees and technical support professionals.
• Business owners and entrepreneurs.
• Professionals working in human resources, operations, and finance.
• Decision-makers within organizations.
• Consultants and business development professionals.
• Employees in government and private sectors.
• Anyone interested in starting a career path in AWS and artificial intelligence.

The Features

• A foundational program suitable for beginners.
• Content covering artificial intelligence, machine learning, and generative AI.
• Focus on practical AI applications within organizations.
• Introduction to AWS AI-related solutions and services.
• No advanced programming experience required.
• Coverage of AI security, privacy, and governance concepts.
• Structured preparation for the AWS AI certification.
• Online course accessible from different regions of Saudi Arabia.
• 40 training hours delivered over 5 days.
• Content suitable for both technical and non-technical professionals.
• Support for developing skills required in digital work environments.
• Delivered by Bader Technology.

Topics

Module One: Artificial Intelligence Fundamentals

• Understanding the concept of artificial intelligence.
• Types of artificial intelligence.
• AI applications and use cases.
• Difference between artificial intelligence and automation.
• The role of data in AI solutions.
• AI applications in business.
• Stages of developing and using intelligent solutions.
• Benefits and challenges of AI adoption.

Module Two: Machine Learning Fundamentals

• Understanding the concept of machine learning.
• The relationship between artificial intelligence and machine learning.
• Types of machine learning.
• Training, testing, and prediction processes.
• Structured and unstructured data.
• Using machine learning for classification and prediction.
• Evaluating model results.
• Factors affecting solution quality.

Module Three: Generative Artificial Intelligence

• Understanding the concept of generative AI.
• How content-generation tools work.
• Foundation models.
• Large Language Models (LLMs).
• Creating text, images, and other content.
• Summarizing and analyzing information.
• Generative AI applications in organizations.
• Advantages and limitations of generative AI tools.
• Reasons behind inaccurate AI outputs.

Module Four: Working with AI Tools

• Writing clear instructions and prompts.
• Defining the required task and context.
• Improving the quality of questions and instructions.
• Specifying the required output format.
• Using examples to improve results.
• Reviewing and evaluating AI outputs.
• Identifying inaccurate responses.
• Gradually improving instructions.
• Effective use of AI tools in the workplace.

Module Five: AI Services on AWS

• Introduction to the AWS environment.
• AI-related AWS services.
• Selecting the appropriate service based on use cases.
• Text and document analysis.
• Image and visual content processing.
• Speech-to-text conversion.
• Building chatbots.
• Recommendation and personalization systems.
• Developing generative AI solutions.
• Managing and operating machine learning solutions.

Module Six: AI Applications in Business

• Improving customer service.
• Automating repetitive tasks.
• Customer sentiment analysis.
• Creating and summarizing content.
• Supporting marketing and sales activities.
• Document analysis.
• Improving internal processes.
• Supporting decision-making.
• Developing products and services.
• Managing organizational knowledge.

Module Seven: Responsible Artificial Intelligence

• Ethical use of artificial intelligence.
• Fairness and reducing bias.
• Transparency in intelligent solutions.
• Explainability of AI results.
• Human review of AI outputs.
• Avoiding harmful content.
• Protecting users.
• Evaluating solution impacts before implementation.

Module Eight: Security, Privacy, and Governance

• Protecting data used in AI systems.
• Managing permissions and access.
• User data privacy.
• Protecting inputs and outputs.
• Managing AI risks.
• Developing AI usage policies.
• Monitoring intelligent solutions.
• Compliance with regulatory requirements.
• Governance and responsibilities within organizations.

Module Nine: AWS AI Certification Preparation

• Understanding the certification’s key topics.
• Learning the question format and structure.
• Connecting concepts with real-world use cases.
• Reviewing essential terminology.
• Practicing scenario analysis.
• Managing review time effectively.
• Identifying knowledge gaps.
• Solving practice questions.
• Creating a complete preparation plan.

Learning outcomes

After completing the course, participants will be able to:

• Understand fundamental artificial intelligence concepts.
• Explain the differences between AI, machine learning, and generative AI.
• Identify AI applications within organizations.
• Understand the role of AWS services in delivering intelligent solutions.
• Use AI tools more effectively.
• Evaluate AI outputs and identify potential errors.
• Understand responsible AI principles.
• Recognize security and privacy risks.
• Participate in AI project planning.
• Communicate effectively with technical teams.
• Select appropriate AI solutions based on business needs.

Requirements And Conditions

• No advanced programming experience is required.
• Previous experience in artificial intelligence is not required.
• Basic computer skills are preferred.
• General knowledge of cloud technologies is preferred.
• Interest in learning artificial intelligence and its applications.
• Ability to understand basic technical terminology.
• Access to a suitable device and stable internet connection.
• Commitment to attending training sessions.
• Allocating time for review and practical application.