Artificial Intelligence Foundation & Intermediate Training

This artificial Intelligence course is designed to help learners decode the mystery of artificial intelligence and its business applications. The course provides an overview of AI concepts and workflows, machine learning and deep learning, and performance metrics. You’ll learn the difference between supervised, unsupervised and reinforcement learning; be exposed to use cases, and see how clustering and classification algorithms help identify AI business applications. Both the Foundation & Intermediate level is combined for the ultimate experience, nevertheless – candidates can choose to just take Foundation level (which is the first 2 days of this program).

  • 3 Days Workshop
  • Completion Certificate awarded by CCSD, UK

  • Please contact us directly for more details


Introduction to Artificial Intelligence

Decoding Artificial Intelligence
Meaning, Scope, and Stages Of Artificial Intelligence
Three Stages of Artificial Intelligence
Applications of Artificial Intelligence
Image Recognition
Applications of Artificial Intelligence – Examples
Effects of Artificial Intelligence on Society
Supervises Learning for Telemedicine
Solves Complex Social Problems
Benefits Multiple Industries
Key Takeaways
Knowledge Check
Fundamentals of Machine Learning

Fundamentals Of Machine Learning and Deep Learning

Meaning of Machine Learning
Relationship between Machine Learning and Statistical Analysis
Process of Machine Learning
Types of Machine Learning
Meaning of Unsupervised Learning
Meaning of Semi-supervised Learning
Algorithms of Machine Learning
Naive Bayes
Naive Bayes Classification
Machine Learning Algorithms
Deep Learning
Artificial Neural Network Definition
Definition of Perceptron
Online and Batch Learning
Key Takeaways
Knowledge Check


Machine Learning Workflow

Learning Objective
Machine Learning Workflow
Get more data
Ask a Sharp Question
Add Data to the Table
Check for Quality
Transform Features
Answer the Questions
Use the Answer
Key takeaways
Knowledge Check

Performance Metrics

Performance Metrics
Need For Performance Metrics
Key Methods Of Performance Metrics
Confusion Matrix Example
Terms Of Confusion Matrix
Minimize False Cases
Minimize False Positive Example
Recall Or Sensitivity
Key takeaways
Knowledge Check
Chat-bot Essentials
What are frameworks to apply on building a chat-bot
What are the do’s and dont’s in enhancing the chat-bot
Machine Learning with Phyton using Scikit-learn(formerly scikits.learn)
Machine Learning Approach
Steps 1 and 2
Steps 3 and 4
How it Works


Steps 5 and 6
Assignment 01
Demo Assignment 01
Supervised Learning Model Considerations
Knowledge Check
Knowledge Check
Key Takeways into Case Study
How Big Data combines with AI to provide smart recommendations
Supervised Learning Models – Logistic Regression
Unsupervised Learning Models
Model Persistence and Evaluation
Knowledge Check
Natural Language processing with Scikit Learn
NLP Overview
NLP Applications
Knowledge check
Scenario Based Examination

Final Examination

What are the course objectives?


Who should take the course?

  • Software developers
  • IT managers
  • Service management professionals
  • Technology Managers
  • IT Managers and CIOs
  • Service Managers (with or without an ITIL background)
  • Service Management Professionals
  • Cloud Strategy and Management Consultants
  • Service Architects, Technical Pre-Sales Consultants
  • IT Business Owners

Who is your trainer for the program?


We offer the following options:

  • Cash
  • HRDF Claimable
  • Maybank Ezpay (Up to 24 months @ 0% Interest)
  • CIMB Easy Pay (Up to 12 months @ 0% Interest)
  • Cash Installment (Case by case basis)

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