Professional Certificate in Applied AI Engineering

Course Overview

Artificial intelligence (AI) is revolutionising entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organisations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. This Professional Course is designed to equip you with the tools you need to succeed in your career as an Artificial Intelligence / Machine Learning / Deep Learning Engineer.

Learning Outcomes

  • Develop skills that are transferrable across all industries: business, information technology, computer science, finance, retail, e-commerce, advertising, manufacturing, healthcare & others
  • Begin your journey as an AI Engineering Specialist in fast-growing & in-demand industries today
  • Become a technology professional experienced in applied AI engineering & analytics

About BAC Digital Academy

We are an industry-certified and recognised training academy. Our panel of subject matter experts have specifically structured the curriculum to focus on current trends and best practices in Data Science & Analytics, and you will have the flexibility of studying anytime, anywhere with our learning management system (LMS).

About Veritas University College

At Veritas, we are constantly re-thinking the learning process and leveraging on efficiency, technology and strategic partnerships to provide a holistic next gen educational journey for our students. As a result of our far-reaching efforts, Veritas has received the BrandLaureate Best Brand in Online Education award for 2020, 2021 and 2022 in recognition of our exceptional academic and co-curricular experience.

Entry Requirements:

  • Malaysian citizens / companies – Job Seekers, Retrenched workers, Fresh Graduates (Diploma/ Degree), Business owners, Entrepreneurs, IT Professionals, etc.
  • Completed Professional Certificate in Data Science & Analytics and/or have some knowledge in programming languages.
  • Participants are also required to bring along their laptops during this course. (Please avoid bringing work laptops that may limit your access to external domains)

Who Should Join this Course?

  • Current Employees/ SMEs/ MNCs/ Start-Ups/ MSMEs & Senior Management
  • Job Seekers
  • Retrenched Workers
  • Fresh Graduates (diploma/degree)
  • Business Owners/Entrepreneurs
  • Malaysian citizens/companies

Course Modules

The modules of this course are designed to give the participant a broad and comprehensive knowledge of Applied AI Engineering. At the end of the course, participants will achieve the following learning objectives listed below for each module.

Introduction to Big Data, AI, ML, DL, and Python Programming Language

  • Understand the meaning of Data Science, Big Data, Artificial Intelligence, Machine Learning and Deep Learning.
  • Understand the differences between Artificial Intelligence, Machine Learning and Deep Learning.
  • Understand the demand for Data Scientists in the current job market.
  • Use Python programming language for Data Science.

Mastering Machine Learning with Python Programming Language

  • Understand how Machine Learning can be used to solve the current issues of Big Data.
  • Understand the types of Machine Learning, and how to use them in the real world.
  • Gain new skills to add to your resume, such as regression, classification, clustering, sci-kit learn, and SciPy.
  • Work on new projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more.

Deep Learning, Neural Networks, & Keras

  • Learn what a neural network is, what a deep learning model is, and the differences between them.
  • Gain an understanding of unsupervised deep learning models, such as auto-encoders and restricted Boltzmann machines.
  • Gain an understanding of supervised deep learning models, such as convolutional neural networks and recurrent networks.
  • Build deep learning models and networks using the Keras library.

Computer Vision and Image Processing

  • Understand the meaning of computer vision, and its application in different industries.
  • Learn about image processing and utilise IT libraries like Pillow and OpenCV.
  • Understand how image classification works.
  • Use project-based learning to create your own computer vision web app, and deploy it to the Cloud

Deep Neural Network with PyTorch

  • Understand how PyTorch library works for Deep Learning.
  • Be able to explain and apply the knowledge of Deep Neural Networks, and related machine learning methods.
  • Use PyTorch library for Deep Learning applications.
  • Build Deep Neural Networks using PyTorch

Deep Learning with TensorFlow

  • Explore the foundational TensorFlow concepts, such as the main functions, operations, and execution pipelines.
  • Learn how TensorFlow can be used in curve fitting, regression, classification, and minimization of error functions.
  • Understand the different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks, and Auto-encoders.
  • Apply TensorFlow for back-propagation to tune weights and biases, while Neural Networks are being trained

Projects with Deep Learning and AI

  • Determine the most suitable kind of deep learning method to use in different situations.
  • Gain practical knowledge on how to build a deep learning model to solve real problems.
  • Master the process of creating a deep learning pipeline.
  • Apply knowledge of deep learning to improve models using real data.
  • Obtain the skills to present and communicate outcomes of deep learning projects

Data Scientist Marketing

  • Understand how platforms like LinkedIn work, and how to build one professionally.
  • Build a competitor portfolio for the projects of Deep Learning.
  • Build a professional resume for job applications.
  • Understand the best techniques to improve and update your LinkedIn profile regularly.

Trainer's Profile

Dr. Mohammed Al-Obaydee

HRDF Certified Trainer: Data Science & Analytics Specialist, Artificial Intelligence Trainer, Entrepreneur

Dr. Obaydee holds a PhD in Artificial Intelligence and is a passionate Trainer and Digital Marketer. His expertise in Big Data Science, Machine Learning, Deep Learning, and Immersive Technology are well-demonstrated in more than 18 years of experience in various Information Technology industries.

To date, he has trained over 2000 participants in Data Science & Analytics and Applied Artificial Intelligence Engineering. With his experience and knowledge in the AI world, Dr. Obaydee aims to bring in the latest technology in digital marketing by using AI, Big Data, Immersive Technology, and Metaverse to leverage social media marketing.

Hello there, welcome to HRD Academy!

< CTA BUTTON <

Tuition Fees

Recommended Courses.

Professional Certificate in FINTECH

The Professional Certificate in FinTech is an intensive instructor-led online training course which dives deep into the fundamentals of FinTech with a focus on practical ‘real-life-‘case studies.

Learn more

Professional Certificate in Data Science & Analytics

This course is designed to help you acquire the concepts, tools, techniques and advanced programming skills (such as Advanced Python & Advanced R) that are essential for a career in data science.

Learn more

Transformative Leadership (5th Discipline)

This program provides for specific tools and exercises to enable the participant to transcend the higher levels of leadership. Participants will also be made aware of their self-imposed barriers which hinder their progress towards becoming a more relevant leader.

Learn more