Professional Certificate in Machine Learning (Deep Learning)

Master the fundamentals and specialised applications of machine learning and deep learning for advanced operational excellence.

In today’s competitive landscape, leveraging machine learning and deep learning is essential for driving innovation, optimising operations, and making data-driven decisions. This course is tailored for professionals and organisations aiming to build robust AI capabilities. Participants will gain hands-on experience in developing, deploying, and managing AI models that can be applied to solve real-world challenges, ensuring operational efficiency and continuous improvement.

This course provides a comprehensive training program that covers both the foundational and advanced aspects of machine learning and deep learning. Participants will learn Python programming and apply machine learning techniques to address complex business problems. The course is designed to ensure that participants can deploy AI solutions effectively within their organizations, with a strong emphasis on real-world applicability and operational excellence.

Programme Objectives

Upon completing the program, participants will be able to:

• Build a strong foundation in Python programming and core machine learning concepts.

• Master the application of supervised, unsupervised, and deep learning techniques.

• Accelerate machine learning computations with advanced GPU and distributed processing methods.

• Implement and manage machine learning models using MLOps workflows.

• Understand advanced model architectures, including autoencoders, transformers, and GANs.

Programme Structure

The course is structured into two intensive modules, followed by a module dedicated to Operational Trials and Evaluation:

Workshop 1: Python Programming and Machine Learning Fundamentals

Duration: 2 days (9:00 AM – 5:00 PM)

Specialised Topics:

• Clean architecture for DataOps

• Builder architecture for machine learning models

• Dashboarding & visualisation principles

• Statistical principles of machine learning and deep learning

• Data analysis violations (e.g., selection bias, assumptions)

• Bootstrapping for misbehaving data

• Supervised ML models (parametric, non-parametric, ensembles)

• Supervised ML workflows with MLOps (registering, tracking, dataset tagging, model promotion)

Workshop 2: Advanced Machine Learning and Deep Learning Techniques

Duration: 2 days (9:00 AM – 5:00 PM)

Specialised Topics:

• Unsupervised ML: From clustering to dimension reduction to deep learning architectures

• Latent space learning and embeddings

• Recommender systems using latent space techniques

• Deep dive into autoencoders (denoising, variational, recurrent, convolutional)

• Specialised architectures (convolutional, recurrent, transformers, GANs)

• Large language models and pre-training/fine-tuning with LoRA weights, adapter layers, prompt tuning

• Agentic workflows (designing multi-hierarchical AI systems)

Workshop 3: Operational Trials and Evaluation (OT&E)

Duration: 2 days (9:00 AM – 5:00 PM)

Focus: Deploying AI models, conducting operational trials, scenario planning, and implementing continuous improvement strategies.

Programme Design

UNIQUELY DESIGNED BY Integrum Global

This program has been meticulously designed in collaboration with Integrum Global, leveraging their deep expertise in AI and machine learning. Integrum’s approach ensures that participants are not only equipped with the necessary technical skills but also understand how to operationalise these skills within their organisations, driving continuous improvement and achieving operational excellence.

Integrum Global is a leading consultancy and technology incubator that specialises in cutting-edge AI solutions, with particular expertise in composable AI and generative AI. The company leverages composable AI to enable businesses to build scalable, modular AI systems that can be customised to meet specific needs, fostering flexibility and innovation. In the realm of generative AI, Integrum Global empowers organisations to create new, AI-generated content, models, and strategies that drive efficiency and creativity. These capabilities are integrated into its AI-driven consultancy services and startup incubation, allowing businesses to adopt and scale advanced AI technologies. Through strategic partnerships, such as its joint venture with Allotrope, Integrum Global is expanding its AI expertise across industries in ASEAN and globally, contributing to sustainable business growth through innovative, AI-powered solutions.

Thanks Dr. Jack. The resources are a great help indeed. Really appreciate it. Want to award you “BEST LECTURER EVER”. As for my current work, they are using R scripts to automate the process of combining excel sheets and then writing to word document to send as daily reports.

Tan Cheng Kiat, Analyst, Healthcare Ministry in Singapore

I have picked up skills working with APIs, data cleaning, data visualisation and data analysis. Projects focused on working with Python 3, Pandas, and Natural Language Toolkit. Both Dr. Ke and Jack are competent, patient and motivating, encouraging us to learn and complete our projects!

Cher Kheng Thian, Founder, Marketing Agency

I say the course curriculum is very focused on training students to handle real-world data analyst work using Python and that the skills learnt will be good enough to support and grow your role as an entry level data analyst.

Ng Yee Tat, Manager, Large Telco in Singapore

Technology Stacks

Faculty

LEARN FROM VETERAN DATA SCIENTISTS/A.I. EXPERTS AND PROFESSIONAL EDUCATORS

JCube faculty have collectively trained more than 10,000 professionals are among the most respected and passionate practitioners and leaders in the field of digital science and transformation. Their expertise provides the highest quality of instruction to learners. Faculty also teach Data Science at renowned Universities at Undergraduate, Masters and Doctoral Levels and are known to be the best teachers who are patient and experienced in simplifying difficult concepts for learners to grasp easily.

DR. JACK HONGPROGRAMME DIRECTOR/LEAD FACULTY

Co-founder of Research Room, an AI consulting and development outfit that delivers decision-making capabilities for complex use-cases, Dr. Hong specializes in developing prediction and decision engines with the use of alternative data. Some of his notable works include omni-channel content personalization systems, manpower resource optimization using deep reinforcement learning, real estate valuation engines, and highly personalized portfolio strategies using applied artificial intelligence (AI). Dr. Hong is concurrently an adjunct faculty with the Singapore Management University (SMU), and has been actively teaching undergraduate, postgraduate, and professional programmes since 2015. He is the lead instructor for the highly acclaimed “Leading Digital Transformation” course for MBA students.

DR. KE JINGHAOCO-LEAD FACULTY

Dr. Ke has led and managed teams to design, construct and maintain corporate governance indices with Singapore Management University (SMU)’s Sim Kee Boon Institute for Financial Economics. He also participated in business consulting and data analytics projects for SMEs through the UOB-SMU Asian Enterprise Institute. He is concurrently adjunct faculty with SMU and he develops course syllabus and instructs Finance and International Finance at the Undergraduate level. Dr. Ke is a full-stack analytics programmer in Python and has also worked with various analytics stacks such as R, SAS, Microsoft Analytics and Stata. Dr. Ke received his Ph.D. in Business (Finance) from SMU in 2015 with his research dissertation and interests in corporate finance, incentives design, social networks, corporate governance and natural language programming.

DR. JONATHAN KHOOCO-LEAD FACULTY

Jonathan Khoo, Ph.D. is a full-stack app developer who likes building stuff. He has published papers in Genetic Programming and has a working paper in Energy Prediction. He has successfully delivered many projects on bespoke implementations of data driven strategies that delivers complex prediction and decision-making capabilities to many large organizations. Khoo obtained his Doctor of Philosophy in Business (Finance) at the Singapore Management University. His dissertation thesis investigates corporate finance through the lens of social network graph analytics, where he found a statistically significant “ownership centrality” effect in firm performance. Prior to that, he completed his Masters in Industrial Engineering and Operations Research at the University of Michigan (Ann Arbor), a year after he received degrees with Highest Honors in Economics and Summa Cum Laude in Electrical Engineering. He is an alumnus of Raffles Institution and Hwa Chong Institution.

Course Fees

SELF-SPONSORED INDIVIDUALS:
S$1600 per pax for a 2 day workshop

CORPORATE RATES:
Less than 8 pax ($11,000 for a 2 day workshop)
8 – 15 pax ($12,000 for a 2 day workshop)

Note: Our course fees are exempt from GST charges.

Policies

1. Cancellation by Client

1.1. Notification:

All cancellations must be submitted in writing via email to admissions@jcube-institute.com.

1.2. Refunds:

– Up to 30 days before the class start date: Full refund minus a processing fee of SGD 800 per class.
– 30 days or less before the class start date: No refund.

1.3. Substitutions:

The client may substitute participants up to 5 days before the class start date without any additional fees.

2. Cancellation by JCube Institute

2.1. JCube Institute reserves the right to cancel the class. In such cases, clients will be notified at least 10 days before the class start date.

2.2. Refunds: In the event of cancellation by JCube Institute, clients will receive a full refund of the class fees.

3. Force Majeure

In the event of circumstances beyond our control (e.g., natural disasters, pandemics, government restrictions), JCube Institute reserves the right to reschedule or cancel the class. Clients will be offered the option to attend on the new date or receive a full refund.

4. Rescheduling

4.1. Client-Initiated Rescheduling: Requests to transfer reschedule the class date must be made at least 14 days before the original class start date. Transfers are subject to availability and a rescheduling fee of SGD 500 per class may be levied.

4.2. JCube Institute-Initiated Rescheduling: If JCube Institute reschedules the class, clients will be offered the option to transfer to the new date or receive a full refund.

5. Attendance Requirements

5.1. Participation: Participants are expected to attend up to 75% of scheduled sessions of the training class to receive any certificates of completion associated with the course.

5.2. Punctuality: Participants should arrive on time for each session. Late arrivals may be allowed at the discretion of the instructor but may result in missing critical content.

5.3. Absenteeism:

– Notification of Absence: If a participant is unable to attend a session, the client must inform JCube Institute as soon as possible. Do note that participants are expected to attend up to 75% of scheduled sessions of the training class to receive any certificates of completion.