Track
New Collar
Duration
30 hours
Skill Level
Beginner
Language
English
About this Course
Learn the core principles behind AI systems, from rule-based logic to data-driven learning.
Learning Mode: Learn at ALC or at Home
Detailed Course Curriculum
Hands-on module breakdown aligned with MKCL production standards and industry requirements.
- Introduction to Artificial Intelligence and Machine Learning
- Objectives
- Introduction to AI
- History of AI
- History of AI
- Definition and its importance
- Definition and its importance
- What is Generative AI?
- What is Generative AI?
- Teaching machines to mimic human intelligence
- Teaching machines to mimic human intelligence
- Understanding the basics of AI
- Concept of ‘Intelligence’
- Concept of ‘Intelligence’
- Machine Intelligence
- Machine Intelligence
- Types of AI
- Narrow AI
- Narrow AI
- General AI
- General AI
- Super intelligent AI
- Super intelligent AI
- Components of AI
- Understanding how machines learn from data
- Understanding how machines learn from data
- Power of ‘Reasoning’
- Power of ‘Reasoning’
- The ability of problem-solving
- The ability of problem-solving
- Discussing how machines interpret sensory information
- Discussing how machines interpret sensory information
- Linguistic Intelligence
- Linguistic Intelligence
- Perception and Computer Vision
- Perception and Computer Vision
- Robotics and Motion
- Robotics and Motion
- Knowledge Representation
- Knowledge Representation
- Planning and Navigation
- Planning and Navigation
- Ethics in AI
- The 3 key areas of AI ethics
- The 3 key areas of AI ethics
- Privacy and data protection
- Privacy and data protection
- Bias and discrimination
- Bias and discrimination
- How to establish AI ethics?
- How to establish AI ethics?
- Sustainability in AI
- Sustainability in AI
- Recap and outcome
- FAQs
- Summary
- Objectives
- Introduction to Machine Learning
- Key components and processes of Machine Learning
- Key components and processes of Machine Learning
- How Algorithms work in Machine Learning?
- How Algorithms work in Machine Learning?
- Applications of Machine Learning
- Applications of Machine Learning
- Benefits and drawbacks of Machine Learning
- Benefits and drawbacks of Machine Learning
- Introduction to Deep Learning
- Artificial Neural Networks
- Artificial Neural Networks
- Structure and components of Artificial Neural Networks
- Structure and components of Artificial Neural Networks
- Overview of Neural Network types
- Overview of Neural Network types
- Benefits and drawbacks of Deep Learning
- Benefits and drawbacks of Deep Learning
- Introduction to Natural Language Processing (NLP)
- Applications of NLP in Machine Learning
- Applications of NLP in Machine Learning
- Introduction to Computer Vision
- Technologies involved in Computer Vision
- Technologies involved in Computer Vision
- Introduction to Cognitive Computing
- Benefits of Cognitive Computing
- Benefits of Cognitive Computing
- Summary
Eligibility Criteria
• Basic knowledge of computers and keen desire to build skills in this field.
• Open to students, job seekers, and working professionals.
• Open to students, job seekers, and working professionals.
Official Certification
• Official MKCL KLiC Certificate upon successful completion of the course and evaluations.
Work-Centric Learning Approach
• Step 1: Learners are given an overview of the course and its connection to life and work
• Step 2: Learners are exposed to the specific tool(s) used in the course through the various real-life applications of the tool(s).
• Step 3: Learners are acquainted with the careers and the hierarchy of roles they can perform at workplaces after attaining increasing levels of mastery over the tool(s).
• Step 4: Learners are acquainted with the architecture of the tool or tool map so as to appreciate various parts of the tool, their functions, utility and inter-relations.
• Step 5: Learners are exposed to simple application development methodology by using the tool at the beginner’s level.
• Step 6: Learners perform the differential skills related to the use of the tool to improve the given ready-made industry-standard outputs.
• Step 7: Learners are engaged in appreciation of real-life case studies developed by the experts.
• Step 8: Learners are encouraged to proceed from appreciation to imitation of the experts.
• Step 9: After the imitation experience, they are required to improve the expert’s outputs so that they proceed from mere imitation to emulation.
• Step 10: Emulation is taken a level further from working with differential skills towards the visualization and creation of a complete output according to the requirements provided. (Long Assignments)
• Step 11: Understanding the requirements, communicating one’s own thoughts and presenting are important skills required in facing an interview for securing a work order/job. For instilling these skills, learners are presented with various subject-specific technical as well as HR-oriented questions and encouraged to answer them.
• Step 12: Finally, they develop the integral skills involving optimal methods and best practices to produce useful outputs right from scratch, publish them in their ePortfolio and thereby proceed from emulation to self-expression, from self-expression to self-confidence and from self-confidence to self-reliance and self-esteem!
• Step 2: Learners are exposed to the specific tool(s) used in the course through the various real-life applications of the tool(s).
• Step 3: Learners are acquainted with the careers and the hierarchy of roles they can perform at workplaces after attaining increasing levels of mastery over the tool(s).
• Step 4: Learners are acquainted with the architecture of the tool or tool map so as to appreciate various parts of the tool, their functions, utility and inter-relations.
• Step 5: Learners are exposed to simple application development methodology by using the tool at the beginner’s level.
• Step 6: Learners perform the differential skills related to the use of the tool to improve the given ready-made industry-standard outputs.
• Step 7: Learners are engaged in appreciation of real-life case studies developed by the experts.
• Step 8: Learners are encouraged to proceed from appreciation to imitation of the experts.
• Step 9: After the imitation experience, they are required to improve the expert’s outputs so that they proceed from mere imitation to emulation.
• Step 10: Emulation is taken a level further from working with differential skills towards the visualization and creation of a complete output according to the requirements provided. (Long Assignments)
• Step 11: Understanding the requirements, communicating one’s own thoughts and presenting are important skills required in facing an interview for securing a work order/job. For instilling these skills, learners are presented with various subject-specific technical as well as HR-oriented questions and encouraged to answer them.
• Step 12: Finally, they develop the integral skills involving optimal methods and best practices to produce useful outputs right from scratch, publish them in their ePortfolio and thereby proceed from emulation to self-expression, from self-expression to self-confidence and from self-confidence to self-reliance and self-esteem!
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