CERTIFICATE IN MACHINE LEARNING

Industry Background

Digitalisation enables a business to produce, adapt and innovate digital technologies and services to enhance wealth creation, productivity, and quality of life. Various latest technology such as Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), collaborative robots (cobots) are becoming very important to Malaysia. During the era of the Industrial Revolution 4.0 (IR 4.0), many corporates in Malaysia started to implement the technologies. BMW Malaysia has implemented automated image recognition. UOB Malaysia has launched Mighty Insights. Ernst & Young using Robotic Process Automation in their business operation. Symprio is using a chatbot design agency to assists in organizations design.

The significance of technology in digitalising Malaysian industries is to innovate business models, reduce operating costs and improve efficiencies and also increased marketing channels to make the marketing promotion ubiquitous says Choon Sen Seah

Paper presented on ”The Significance of Technology in Digitalising Malaysia Industries” on February 2021 in the Conference on Management, Business, Innovation, Education and Social Science

Machine Learning & Artificial Intelligence (AI) is everywhere – making its way into various facets of our daily lives without us even knowing it. From banking to manufacturing industries, and even simple things like the autocorrect features and chatbots that we regularly encounter, AI has played a big role in shaping our society today.

In time, more and more devices will come with the ability to grasp, contextualize, and recognize images, acquire and build knowledge through deep learning, and teach themselves how to comprehend speech and understand us when we communicate with or using Machine Learning & AI

The Value To The Industry

Machine learning is a form of AI that enables a system to learn from data rather than through explicit programming. However, machine learning is not a simple process. As the algorithms ingest training data, it is then possible to produce more precise models based on that data. A machine-learning model is the output generated when you train your machine-learning algorithm with data. After training, when you provide a model with an input, you will be given an output. For example, a predictive algorithm will create a predictive model. Then, when you provide the predictive model with data, you will receive a prediction based on the data that trained the model.

Machine learning offers potential value to companies trying to leverage big data and helps them better understand subtle changes in behavior, preferences or customer satisfaction. Business leaders are beginning to appreciate that many things happening within their organizations and industries can’t be understood through a query. It isn’t the questions that you know; it’s the hidden patterns and anomalies buried in the data that can help or hurt you.

Machine learning is changing the world by  transforming all segments including healthcare services, education, transport, food, entertainment, and different assembly line and many more. It will impact lives in almost every aspect, including housing, cars, shopping, food ordering, etc.

According to PWC, machine learning in economics  can increase productivity by up to 14.3% by 2030. Machine learning is a catalyst for productivity growth. Soon, many current jobs and tasks will be performed totally by machine learning and Artificial Intelligence algorithms or with usage of them

The iterative aspect of machine learning is important because  as models are exposed to new data, they can independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. … Machine learning applications for everyday life.

Why Machine Learning Is Crucial

Computer scientists are required in the development of Machine Learning, Deep Learning and AI since they must monitor how the system reacts to various factors. When the machine observes new scenarios, the computer scientist must be able to advise it on what to do.

This is one of the reasons why these technologies will provide new employment while simultaneously eliminating some. Repetitive tasks, such as assembly line labour, will be the first to be replaced by AI.

The Malaysian government expects the National Industrial Revolution 4.0 (IR4.0) policy to improve the country’s productivity by 30% across all sectors by the end of 2030, and Machine Learning, Deep Learning & AI is a significant part of that. According to Dzuleira Abu Bakar, CEO for Technology Park Malaysia (TPM)highlighted through ASEAN, Malaysia has access to a market of 630 million people, and a GDP of US$3 trillion (RM12.6 trillion). The ASEAN market is expected to skyrocket to US$5.2 trillion (RM21.8 trillion)by 2025.

https://www.digitalnewsasia.com/business/ai-opportunity-malaysia-catch-or-slip-behind

Demand For Employment

There are tremendous economic and productivity gains resulting from AI. According to Mckinsey 50% of work time in Malaysia is spent on repetitive activities that are highly automatable. AI can automate routine tasks, augment employees’ capabilities, and allow time to focus on more stimulating and higher value-adding work. With increased automation, AI can potentially create 6 million new jobs by 2030 in Malaysia and this future of work will create new needs for skills and long-term learning in nearly every part of the workforce. http://www.mckinsey.com/featured-insights/asia-pacific/automation-and-adaptability-how-malaysia-can-navigate-the-future–of-work

An entry-level Machine Learning Engineer with less than 1 year experience can expect to earn an average total compensation (includes tips, bonus, and overtime pay) of RM 48,543 per annum. An early career Machine Learning Engineer with 1-4 years of experience earns an average total compensation of RM 53,500 per annum https://www.payscale.com/research/MY/Job=Machine_Learning_Engineer/Salary

The Programme

Machine Learning & Deep learning computer algorithms go through a similar process to a child learning to recognise a dog. Each algorithm in the hierarchy performs a nonlinear transformation on its input before generating a statistical model as an output. Iterations continue until the result is accurate enough to be useful. The word deep was motivated by the amount of processing layers that data must flow through. The programme will expose you to various aspects of computer networking, software development and more.

Programme Objective

• Demonstrate Activation functions and Optimizers in detail with hands-on 
• Demonstrate intuitively convolutional neural networks for image recognition 
• Design and construct a neural network from simple to more accurate models 
• Understand recurrent neural networks, its applications and learn how to build these solutions 
• Understand hyper-parameters and tuning 

Pogramme Learning Outcome

• Articulate the core architecture and API layers TensorFlow 
• Construct a computing environment and learn to install TensorFlow 
• Develop TensorFlow graphs required for everyday computations 
• Use logistic regression for classification along with TensorFlow
• Develop, design and train a multilayer neural network with TensorFlow 
• Learn how to build industry’s leading uses cases eg, Recommendation systems, Speech recognition, commercial grade Image classification and object localization etc…. 
• Lead ML/DL projects based on TensorFlow implementation  

Programme Delivery Methodology:

• Face to Face or Online Training
• Practical/ Lab Exercise
• eCoaching

Duration

3 or 5 days

Entry Requirement

Basic understanding of IT

Assessment Method

Candidates will need to sit for computerized examination for 1.5 Hours and the various practical exercise

Learning Materials

There will be a student manual and lab workbook for each participants provided by US Council

Course Materials

 

CERTIFICATION BODY

The Cyber Security and Information Technology (CIIT) market presence, be it among the practitioners or manufacturers is highly volatile, constantly evolving and progressing at such an exponential rate of development, innovation and advancement. Therefore, if CTOs, CSOs, CISOs, IT Managers, Cyber Managers, IT Directors, Information Risk Directors and Cyber/Information Technology Consultants and practising Professional do not keep in tap or remain within the pace of changes and development they then would become obsolete or redundant within their own organisation and therein cripple the existence and survival of their organisation to the onslaughts and offensive penetration of the dark and deep web perpetrators.

Likewise businesses will have to adopt and adapt to the fast pace changes and unpredictability of impulsive threats. Organisations need to be constantly vibrant and robust enough to withstand the unscrupulous and crooked radicals who are out there to paralyse the operational functionality of the Information technology of the company and deceitfully siphon information and critical data via the organisation’s cyber security loopholes and gaps.

As such, Cyber Security and Information Technology (CIIT) becomes a vital and critical component of the business facet. It is a very domineering and imperative business issue for all companies, corporations and government agencies today irrespective of the size or volume of business. Cyber criminals and delinquents are sprouting any and everywhere. Their embryonic destructive activities are bringing organisations to their knees for answers to counter and thwart the offensive cyber and IT threats.

Therefore CIITnet acts as the gateway as well as gatekeeper for Cyber Security Intelligence and Information Technology parameters, fraternity, practitioners as well as the organisations to which they represent. CIITnet is the very engine which will propel the mechanics and net web of the Cyber Security Intelligence and Information Technology agenda, driving the essence of Cyber Intelligence to the front and push the issues right to the top of concerns among the professionals who make the decision to drive the robust pathway of the Information Technology charter, framework, imprints and support network of the organisation.

CIITnet’s origin was initially a conceptualisation among a few out of the box thinking Cyber Intelligence and Information Technology nerds whose eagerness and carving to “fight the devils” in the cyber world lead them to turn their concepts to formalise an entity to pin in their huge craving for a change in the approach to the battle and war against cyber and IT crime. The aim was a yearning to get the entire circle of CTOs, CSOs, CISOs, IT Managers, Cyber Managers, IT Directors, Cyber/Information Technology Consultants, Information Risk Directors as well as any and everyone who touch base with the cyber and IT world to get into a network of collaboration.

The intent was to nurture, develop and encourage a cohesive effort of merging everyone’s thinking and practicalities to build a defence so strong that criminals and attackers can no more try to be in the front but lack behind on their possibilities to thwart the strength which can be built up by being together and working hand in hand to push the culprits beyond the cliff.

This steered the nerds and geeks to converge and form a group among themselves and cracked their brains to find the right alchemy and transformation for cyber intelligence and information technology. The resultant which came to reality today is the Board of Eminence, spearhead by one in prominence and come out of the anonymity and namelessness and formed CIITnet and began to bring recognizability to this network. Today, CIITnet has become alive as an authentic entity and the ordinariness is a foregone thought and the distinctiveness, significance and worth as an organisation is gaining momentum among the professionals and practitioners around the world.

Yes, the drive and thrust is gaining fast traction for CIITnet. Simultaneously, the passion and desire to bring it to a worldwide recognition is definitely the ultimate mission of the CIITnet Board of Eminence whose vision is beyond the horizon. The rage to winning the war against cyber and IT crime is so great that the propulsion of CIITnet will not just be a murmur in the customary normal stratum but a big bang among Cyber Intelligence and Information Technology professionals and practitioners. CIITnet is manifesting its presence internationally as it is already making signs and signals of it. The variety of plans and projections as well as a huge portfolio of cyber security intelligence and information technology facets of CIITnet is creating a huge presence that reaching globally is no more a dream but a reality.

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