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Choose Artificial Intelligence & Machine Learning Course in Malaysia

Completely project-based Artificial Intelligence & Machine Learning Course.

Course Price

RM 4,000

RM 3,000

Mdec Digital Up Initiative 2023

Limited Time offer


The participants must pay to Nexperts Academy Sdn Bhd RM 3000 first. Once training completed, MDEC will reimburse to participant’s account RM 2500 within 30.09.2023.

Speak with our Course Advisor

Duration: 5 days/40 hours live instructor-led training.


AI is projected to become the most sought-after job in the near future, presenting promising career prospects for IT professionals.

According to IDC, spending on products and services incorporating Augmented Reality (AR) and Virtual Reality (VR) concepts is expected to grow significantly, reaching nearly 215 billion by 2021.

The rise in demand for AI professionals is a positive sign for individuals aspiring to build a career in this field.

The course offered covers the foundational aspects of modern AI and explores various applications of AI.

 Students will gain in-depth knowledge of essential AI concepts, including heuristic search and genetic programming.

 The curriculum focuses on practical aspects like game development and building intelligent applications to address real-world challenges in organizations and businesses.

 The course aims to ignite enthusiasm among students about the vast array of applications and opportunities in the AI field, pushing the boundaries of human capabilities.

 The rapid expansion of AI in various industries continues to open up new possibilities and avenues for innovation.

 By completing this course, students can equip themselves with the skills and expertise necessary to tap into the growing AI job market and contribute to the advancement of AI technology.

 Overall, the course prepares students to explore and embrace the limitless potential of AI and its impact on the future.


Complimentary Google Tensorflow Certified Developer

Instructor-led live classroom

Interact with instructors in real-time— listen, learn, question and apply. Our
instructors are industry experts and deliver hands-on learning.
Mentored by industry leaders
Learn from the best in the field. Our mentors are all experienced professionals in
the fields they teach.
Advance from the basics
Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.
Learn through doing
Learn theory backed by practical case studies, exercises and coding practice.
Get skills and knowledge that can be effectively applied.
Curriculum designed by experts
Our courseware is always current and updated with the latest tech
advancements. Stay globally relevant and empower yourself with the training.
Code reviews by professionals
Get reviews and feedback on your final projects from professional developers.

Criteria to apply

Be Trained & Claim 95% Fee before 30.09.2023

  • Open to Malaysians, Employed, Unemployed, Fresh Graduates, OR Gig workers aged 21-55 years old.

  • Be trained in any of our courses listed in the directory from 1 March 2023 – 30 September 2023.

  • You can get reimbursement of up to RM2,500.00 on the training fee. You are required to submit documentation for the claims.

  • Subject to availability and on a first come first served basis.

How to apply for Incentive

Step 1

Complimentary 30 hours on fundamentals of machine learning full course video

Step 2

Register for the course

Step 3

Make payment of the Training Fee

  • RM 4200

  • RM 3000

Step 4

Attend training (Live Online / Classroom)

Step 5

Submit Application to obtain reimbursement of training fee of RM2,500 from

Step 6

Upon receipt of approval by Mdec you will receive the incentive amount within 30 days.



In the digital era, organizations are reinventing their advertising strategies to better engage and connect with their customers. This path will equip you with the skills, insights and digital understanding to be a particularly effective digital marketer and generate a measurable effect on your company’s backside line.



Machine Learning Techniques

o Realize different classification and regression techniques.

Deep learning algorithms

o See how to use deep learning algorithms and build applications based on it

Reinforcement Learning

o Learn how reinforcement learning creates an environment

Natural Language Processing

o Learn the basics of text processing in Python.


o Understand the concept of clustering and how to use it to automatically segment data.

Build intelligent systems

o Discover how to build intelligent applications centered on images, text, and time series data.

Building Games

o Understand the basics of heuristic search and genetic programming, develop AI games.

Real-time Object Detection

o Learn to detect objects and extract feature to implement operations in real-time



Data Analyst

Developers Who Want to Transition to AI

Students Interested in Making a Career in AI

IT Professionals Aspiring to Enter Data Science and AI



This course introduces the student to Python language.

Upon completion of this class, you will be more than comfortable to write Python programs.

Through this course, you will:

  • Have an insight on features of Python that make it an excellent choice for projects of virtually any size.

  • Understand the distinctions between Machine Learning, Deep Learning, and Artificial Intelligence.

  • Discover how AI and deep learning algorithms are used now.

  • Build the simplest Machine Learning models possible.

  • Machine Learning models can be predicted and developed.



  • Fundamentals of Python language

  • Writing Python codes and program

  • Build and run project based on Python

  • Create your own applications for data retrieval, processing, and visualization

  • Data Science Libraries

  • Machine Learning

  • Machine Learning Algorithms

  • Artificial Intelligence



  • Comprehensive Blended Learning program

  • Flexible access to online classes

  • Instructions carried out through industry experienced trainers

  • Interactive Quizzes

  • 15+ in-demand technologies and skills

  • Get hands-on experience with four industry-related projects

  • 24x7 learner assistance and support



The admission fee for this full-stack web development certification program is RM3000.

Duration: 5 days/40 hours



  • Physical Classroom Training (Malaysia)

  • On-site Company Training (Malaysia)

  • Online Training via Microsoft Team (Malaysia and International)



  • Beginners in AI and Machine Learning.

  • Python beginners who are interested in machine learning.



The inquiry process comprises three simple steps.

  • Submit Inquiry- Tell us a bit about yourself and the questions you want to enquire

  • Reviewing–Your questions will be processed and answered within a day or two 

  • Response–Answers will typically be sent through email. However, you may tell us the option you prefer us to contact you in



Foundations of AI

Learning Objectives

Learn how to build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you. Develop expertise in popular AI & ML technologies and problem-solving methodologies. Also develop the ability to independently solve business problems using Artificial Intelligence & Machine Learning.

Topics Covered:

  • Write Python code to analyze, manipulate and visualize data

  • Learn to implement statistical techniques with Microsoft Excel

  • Write Python code using Python library – matplotlib, seaborn to visualize data and represent it graphically

  • Conduct exploratory data analysis in python to identify potential revenue maximization opportunities and also visualize data

Machine Learning – Supervised Learning

Learning Objectives:

Learn about supervised learning techniques – regression and classification. Also understand various techniques to build Decision Trees.

Topics Covered:

  • Regression (Linear, Multiple and Logistic)

  • Classification (K-NN, Naive Bayes) Techniques

  • Decision Trees

  • Case Study


Hands On:

This dataset classifies people described by a set of attributes as good or bad credit risks. Using classification techniques, build a model to predict good or bad customers to help the bank decide on granting loans to its customers.

Machine Learning – Unsupervised Learning

Learning Objectives:

Learn about unsupervised learning technique – K-Means Clustering and Hierarchical Clustering. Also understand the Elbow method and Silhouette method.


Topics Covered:

  • K-means Clustering

  • Hierarchical Clustering

  • High-dimensional Clustering

  • Case Study


Hands On:

In marketing, if you’re trying to talk to everybody, you’re not reaching anybody. This dataset has social posts of teen students. Based on this data, use K-Means clustering to group teen students into segments for targeted marketing campaigns.

Machine Learning – Ensemble Techniques

Learning Objectives:

Learn about bootstrap sampling and its advantages followed by bagging. Boost model performance with Boosting. Through a real-life case study, learn Random Forest and how it helps avoid overfitting compared to decision trees.


Topics Covered:

  • Bagging

  • Boosting

  • Random Forest

  • Case Study


Hands On:

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. In this case study, use AdaBoost, GBM & Random Forest on Lending Data to predict loan status. Ensemble the output and see your result perform better than a single model.

Machine Learning – Reinforcement Learning

Learning Objectives:

Understand the basics of RL and its applications in AI. Get an understanding of Markov Decision Processes: Model processes as Markov chains, and learn algorithms for solving optimisation problems. Write Q-learning algorithms to solve complex RL problems.

Topics Covered:

  • Value based methods

  • Q-learning

  • Policy-based methods


Hands On:

In marketing, if you’re trying to talk to everybody, you’re not reaching anybody. This dataset has social posts of teen students. Based on this data, use K-Means clustering to group teen students into segments for targeted marketing campaigns.

Deep Learning

Learning Objectives:

  • Learn advanced machine learning techniques using the Neural Networks algorithms. Neural Networks can enable pattern recognition based on a large amount of inputs. Learn how NN algorithms work, and end up with an introduction to deep learning.

  • This module covers various activation functions like sigmoid, hyperbolic-tangent, Rectified Linear Units, Leaky Rectified Linear Units.


Topics Covered:

  • Neural Network Basics

  • Deep Neural Networks

  • TensorFlow using Neural Networks & Deep Learning

  • Case Study


Hands On:

A research study was aimed at the case of customers’ default payments in Taiwan. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default will be more valuable than the binary result of classification – credible or not credible clients.

Natural Language Processing

Learning Objectives:

Get started with the Natural language toolkit, and learn the basics of text processing in Python. Learn how to extract features from unstructured text and build machine learning models on text data. Conduct sentiment analysis, learn to parse English sentences and extract meaning from them. Explore the applications of text analytics in new areas and various business domains.


Topics Covered:

  • Statistical NLP and text similarity

  • Text Summarization

  • Syntax and Parsing techniques

  • Semantics and Generation

  • Case Study


Hands On:

Stock market prediction has been an interesting research topic for many years. Finding an efficient and effective means of studying the market perceptions found its way in different social networking platforms such as Twitter. With proper tools and the help of technology, meaningful and precious information can be gathered, analyzed, and utilized in different areas like in the movement and performance of the stock market.

Computer Visions

Learning Objectives:

Learn to use the power of computer vision and play with what you see, detect faces, eyes and other attributes using Haar cascades.


Topics Covered:

  • Convolutional Neural Networks

  • Keras Library for Deep Learning in Python

  • Pre-processing Image Data

  • Object and face recognition using OpenCV

  • Case Study


Hands On:

While we drive on a highway, we tend to feel sleepy. In this project, using OpenCV and implementing object detection and feature extraction we detect fatigue in real-time and report an alarm which will not only keep a driver attentive while driving but also reduce the number of accidents.

Intelligent Agents

Learning Objectives:

Learn the AI search technique that employs heuristic for its moves. Understand the fundamental concepts of genetic algorithms and visualize the evolution.


Topics Covered:

  • Uniform and heuristic-based search techniques

  • Planning and constraint satisfaction techniques

  • Adversarial search and its uses

  • Case Study


Hands On:

Use cutting edge AI techniques to teach a computer to play a computer game.

Here are the best part of what will you get from this course

We will build AI Product as part of our project

 We will solve real world problems with AI

 Build machine learning models that can do prediction

 Master AI models

 Complimentary 30 hours on fundamentals of deep learning full course video

 Complimentary 30 hours on fundamentals of machine learning full course video



What are the prerequisites to take this course?

Beginners are welcome to join. Basic programming knowledge is recommended.

Do you provide support for this course?

Yes, our trainers are there to support you during training and post training.  

Can I become a programmer right away after completing this course?

Absolutely not. It takes time, practice and experience to become one. However, with this course and all the hands-on training, we will give you real time experience used in industries, sufficient for you to start preparing for job interviews. 

Will I receive a certificate upon finishing this course?

Yes, you will get a personalized digital certificate downloadable as a PDF. You will need to complete over 85% of the curriculum lessons

Which is the best AI & ML training company in Malaysia?

Nexperts Academy is the best in Malaysia. Our google rating is an evident of our strength in this field.

Can I request a refund if I am not happy with the training?

Yes, subject to our refund policies.  






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