Sail() logo

Courses

Building Careers Through Cutting-Edge Technology Education.

In today's job market, learners need more than just theoretical knowledge; they need practical skills and hands-on experience with the latest technology. Sail() delivers industry-aligned courses designed with clear learning objectives to equip learners with the expertise needed to advance their career. Explore our course offerings and empower your future.

Prepare your students for the future of tech with our specialized training pathways in cloud computing, data science, and AI/ML.

NoviceBeginnerIntermediateAdvanced
Cloud Computing
Pathway		Introduction to ComputingCloud AdministratorPractical Programming with PythonCloud DevOps EngineerCloud DeveloperCloud Native Application Developer
Data Science
Pathway		Cloud AdministratorPractical Programming with PythonData EngineerData Scientist
AI/ML
Pathway		AI UserCloud AdministratorPractical Programming with PythonData EngineerAI PractitionerAgentic AI

Sail(AI User)

A sophisticated AI User has a solid grasp on where tha AI/ML based systems are being used successfully nowadays, where are the limitations, and what is the role of data in such systems.

Course Description:

In this course, learners develop their knowledge and skills to become informed users of modern artificial intelligence (AI) and machine learning (ML) based systems. They gain knowledge and insight into AI/ML domains, AI/ML application capabilities, how AI/ML applications achieve their objectives, and potential AI/ML limitations. Learners engage with concepts and practice hands-on skills to operate various AI/ML-powered systems in relevant application areas. Learners will be able to identify long-term growing trends in the deployment of AI/ML-enabled automation, current capabilities / limitations, and typical sources of error. Additional topics include the role data plays in AI/ML-powered applications, how to validate and troubleshoot such applications, how to identify when an AI/ML system fails, how to identify inherent biases and issues with fairness within available data and mitigate their effects during decision-making, as well as the impact of computing devices and environments AI/ML systems run on.

Prerequisites:

  • Introduction to Computing

Duration:

  • 8 modules
Get the syllabus template

Learning Objectives

Learners who complete the AI User course should be able to:

  • Interact with different types of AI systems and recognize their capabilities and limitations.
  • Explain the effects of data quality, quantity, and representativeness on the performance of ML systems.
  • Inspect, validate, and critically assess the outputs of AI systems.
  • Analyze plausible AI system outputs from different areas, such as language technologies and computer vision, including state-of-the-art generative models.
  • Discuss the advantages and disadvantages of different computing devices and environments for the deployment of AI systems.
  • Explain ethical and responsible practices in AI, promoting informed and conscientious use of AI technology.