BE A CERTIFIED DATA SCIENTIST TODAY!

WORLD’S FIRST AND ONLY BELT SYSTEM AI TRAINING

Are you looking to acquire highly sought after skillsets that will earn you a one of the highest paid jobs in the world today which will keep organizations competitive and sustainable through digital transformation and the post-covid era?

Want to be certified by an organization that has access to many real jobs and job opportunities in Machine Learning?

Want to complement your skillsets with cutting-edge Analytics and Machine Learning skills to immediately enhance your value to your organization?

Cannot afford the time to take a long, rigid and expensive offline Analytics and Machine Learning course taught by non industry practitioners?

Worried that you have no experience in computing or math or disadvantaged by those who have studied computer science before to start building a career engine in Analytics and Machine Learning?

Confused by the deluge of Data Analytics and Machine Learning curriculum in the market today?

If your answer is yes to one or more of the questions above, then this is the certification for you.

WHAT YOU REALLY NEED TO LEARN TO BE A DIGITAL SCIENTIST IN APPLIED MACHINE LEARNING

A competent Digital Scientist in Machine Learning (or A.I.) highly coveted by many organizations today is one who knows how to formulate and implement data and artificial intelligence (AI) or Machine Learning strategies to optimise business value that are derived from valuable data assets. They are fundamentally grounded in permanent “principles” of Data Science and are not distracted by the deluge of tools in the market today. Competent Digital Scientists today are familiar with the existing solutions available in the market and are equipped to learn new scripting, programming languages and platforms on the fly. In addition, they are Digital Masters who are able to recommend and deploy the relevant and most cost efficient platforms and AI/Machine Learning solutions to address the business issues and challenges faced by the organization and to roadmap and create new industries of the future.

DESIGNED WITH YOU IN MIND BY INDUSTRY VETERAN Ph.Ds

Uniquely designed by veteran Ph.Ds who are industry masters in the craft of analytics and machine learning at JCube Institute; and supported by a network of experienced data science/machine learning experts and corporate sponsors, JCube Institute aims to equip individuals today with a strong foundation in Data Analytics and Machine Learning starting with Python programming, and subsequently with the ability to master digital-first thinking, create strategies and roadmaps for existing and new industries of the future.

It is designed to develop in you in genuine Data Science capabilities in the most efficient way unlike many courses both offline and online that are expensive, time-consuming, bloated and designed to train you to be a one man digital team, batteries included.

CAREER OUTCOMES/SCHOLARSHIPS

JCube is confident that every certified individual will be well equipped to either advance their careers in their existing jobs or find a new opportunities in Digital Jobs as digital scientists at top organizations like Certis, Google, Tesla, amongst others. Placement opportunities and scholarships will also be available for selected candidates.

DIVERSE BACKGROUNDS WELCOME

Students are not required to have a bachelor’s degree in a science or math discipline, or work experience in a technical field. As part of the course, students will be undergoing Python 3 programming training to develop the foundations to undertake projects at a later stage of the certification.

INDUSTRY CERTIFIED BASED ON REAL_WORLD PROJECT WORK

While other data science programmes focus on Computer Science theory, this certification equips students with practical industry coveted skillsets and subsequently transformative leadership with an end-to-end perspective on data science and machine learning. Students are prepared to solve real-world problems through expertise on contextual inquiry, data visualization, and presentation and will be certified later based on real-world implementation of projects.

LEARN FROM VETERAN DATA SCIENTISTS AND A.I. EXPERTS

JCube faculty are among the most respected and passionate practitioners in the field of digital science and transformation. Their expertise provides the highest quality of instruction to learners. Faculty also teach Data Science at reowned 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.

REVOLUTIONARY TRAINING METHODOLOGY AND COACHING

Well-rounded training that covers both managerial and technical aspects throughout the entire certification process. Students learn the entire digital science value chain right from the start. Subsequent belts are focused at increasing the level of mastery of each component of the data science value chain. Students are grounded in digital science foundations and trained to learn new ‘forms’ and tools such as Python, Scikit-learn, Tensorflow, Pytorch, etc, on-the-fly. Course is short and compact, targeted to get you industry ready and certified within the shortest time and working around your busy schedule.

Faculty

DR. JACK HONG
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). He is also AI Technology Consultant at Certis Group, Data Science Advisor at Vertex Holdings, advising on Human Conversational AI, Predictive Resource Allocation, Super-Intelligence in Natural Language Capabilities in Finance. He is also CEO of Integrum Global.

Adjunct faculty with the Singapore Management University (SMU), and has been actively teaching undergraduate, postgraduate, and professional programmes since 2015. He is also the lead faculty for the highly acclaimed “Leading Digital Transformation” course for MBA students.

DR. JONATHAN KHOO
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 signifant “ownership centrality” effect in firm perfomance. 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.
DR. KE JINGHAO
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.

Course Details

JUNE 2023

21 hours on-site classroom (6 sessions of 3.5 hours each)
100 hours online (self-study+projectwork) and
20 hours personalised e-coaching

Normal Normal price SGD 4,500
After subsidies, SGD 2,500*

*Additional Corporate Learning Grants available on request

At local premises at CTHub 2

Schedule

Run 1 Schedule:

Class 1: 01/06/20 (7 p.m to 10 p.m)
Class 2: 03/06/20 (7 p.m to 10 p.m)
Class 3: 15/06/20 (7 p.m to 10 p.m)
Class 4: 17/06/20 (7 p.m to 10 p.m)
Class 5 : 29/06/20 (7 p.m to 10 p.m)
Class 6 : 01/07/20 (7 p.m to 10 p.m)

Participants continuing Certified Data Analyst, please click Certified Data Analyst for more training dates.

Run 2 Schedule:

Class 1: 02/06/20 (7 p.m to 10 p.m)
Class 2 : 04/06/20 (7 p.m to 10 p.m)
Class 3: 16/06/20 (7 p.m to 10 p.m)
Class 4: 18/06/20 (7 p.m to 10 p.m)
Class 5: 30/06/20 (7 p.m to 10 p.m)
Class 6: 02/07/20 (7 p.m to 10 p.m)

Participants continuing Certified Data Analyst, please click Certified Data Analyst for more training dates.

Participants who complete Certificate in Python Programming may continue their certification with the following classes

Class 7: 13/07/20 (7pm – 10.30pm)
Class 8: 15/07/20 (7pm – 10.30pm)
Class 9: 27/07/20 (7pm – 10.30pm)
Class 10: 29/07/20 (7pm – 10.30pm)
Class 11: 11/08/20 (7pm – 10.30pm)
Class 12: 12/08/20 (7pm – 10.30pm)
Class 13: 24/08/20 (7pm – 10.30pm)
Class 14: 26/08/20 (7pm – 10.30pm)

Participants who complete Certified Data Analyst may continue their certification with the following classes

(To be confirmed)

Class 15: 03/11/20 (7pm – 10.30pm)
Class 16: 05/11/20 (7pm – 10.30pm)
Class 17: 17/11/20 (7pm – 10.30pm)
Class 18: 19/11/20 (7pm – 10.30pm)
Class 19: 01/12/20 (7pm – 10.30pm)
Class 20: 03/12/20 (7pm – 10.30pm)
Class 21: 15/12/20 (7pm – 10.30pm)
Class 22: 17/12/20 (7pm – 10.30pm)

Belt System

  • 1st and only Belt grading system in the world for A.I. Training
  • Well defined learning and certification progression via the Belt grading system
  • Students learn the entire digital science value chain and progress to higher level belts through mastery.
  • Completion of our higher Belt masteries requires students to complete real projects from our industry partners.
  • Completion of these real projects will automatically enhance your employability with these industry partners as future employers.
  • Our Belt system is recognised in the industry and attestation of your skill competency.

Job of Head of Data Science/A.I.

The Head of Data Science and Artificial Intelligence formulates and implement data and artificial intelligence (AI) strategies to optimise business value derived from data assets. He/She guides the AI research direction to create new algorithms and models, and reviews the feasibility of translating research and development outcomes into data and AI solutions. He/She oversees the development of data and AI solutions for the business to inform strategy and planning, decision-making and drive performance. He/She identifies potential intellectual property commercialisation opportunities for AI solutions and/or models, and oversees the preparation and application for intellectual property rights He/She manages a team and is proficient in statistics, scripting and programming languages required by the organisation. He/She is also familiar with the relevant software platforms on which the solution is deployed on. The Head of Data Science and Artificial Intelligence is a highly effective communicator, articulating the potential value and impact of data and AI solutions on the business and influencing key business stakeholders. He is a proactive and innovative individual, possessing a strong drive to succeed amidst an evolving business environment. He develops the data and AI team’s technical and leadership capabilities, and ensures compliance to the organisation’s data privacy policies, ethics and governance framework, and intellectual property legislation.

Curriculum/Topics

With many years of project and digital leadership experience at large and small corporations, we have revolutionised Data Science and Machine Learning training at JCube. Through this programme, we aim to establish strong data science foundations in students and to train students to pick up new tools and forms by themselves. This course is different from all other courses in the market in that it is short, compact and targeted at coaching and helping you to pick up practical industry coveted skillsets and thereafter transformative leadership with an end-to-end perspective on data science and machine learning.
After the foundational topics are covered, our faculty will introduce more cutting-edge topics and use-cases that are used in many real-life organizations today as participants progress further in the belt system. These include the inculcation of new digital drivers of disruptive businesses through frameworks, toolkits such as A.I. project canvas, A.I. Solutions Architecture, Digital Business Model Canvases, etc. You will learn through discussions and projects and will be skilled in the introduction of the essential building blocks of digital-first thinking to transform business value propositions, improve decision making, optimize organizational structures and processes, and create a new working culture that is needed for a digital-first organisation. Applying Machine Learning and Deep Learning principles, you will be ultimately be trained to synergise what you have learnt and collectively create applied and implementable strategies and roadmaps for existing and new industries of the future.

PYTHON PROFICIENCIES

Python is the primary programming language used throughout this curriculum. Students will be awarded a Certificate in Python Programming after they complete their basic Python training. Topics covered include: Object-oriented Programming, Parallel and Distributed Computing using Celery, Dask.

DATA PROFICIENCIES

Linear Algebra (Vectors/matrices, linear combinations, Numpy), Data techniques such as inspection/cleaning, transformation and imputation, Object Relational Mapping using SQL Alchemy and Django, Web and API scraping techniques.

STATISTICAL FOUNDATIONS

Descriptive Statistics, Probability (Binomial, Conditional and Bayesian), Distributions and confidence intervals, law of large numbers and Central Limit Theorem.

RESEARCH DESIGNS

Hypothesis testing designs, model identifications, Causality models (Instrumental variables and 2 stage setup, Selection models, Regression Discontinuity Design, Factor Analysis, Structural Modelling), domain research and proxy tools

PREDICTIVE MODELLING

Linear Regression, Decision Trees, Clustering, Multi-layer perception and feed forward neural networks (Deep learning). Ensembles, convolutional neural network, long-short term memory, transformer, autoencoders, natural language processing, social network analytics, computer vision.

DECISION MACHINES

Optimisation – Optuna, Reinforcement Learning, OpenAI Gym, Transfer Learning, Federated Learning

OPERATIONS

DevOps, Machine Learning Operations (MLOps)

DIGITAL TRANSFORMATION/DIGITAL-FIRST THINKING (BLACK BELT)

Agile Principles, SCRUM, Value Transformation Roadmaps, Digital Business Models, AI Project Canvas, AI Solutions Architecture, Cybersecurity Frameworks, Change Management Tools such as Force Field Analysis, Lean Transformation Roadmaps amongst others.