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AI Fundamentals Training [Understanding Machine Learning & Deep Learning]

Understanding what technologies make up AI and thinking about how to apply them

Equip your team to reclaim their time and increase their output. This training is for organizations that want their teams to stop doing "busy work" and start being more effective. Instead of just talking about the theory of AI, your employees will learn to identify the repetitive, manual tasks in their daily workflow that can be handled by technology. By understanding what AI is actually capable of, your team will gain the tools to streamline their own processes, reduce errors, and focus their energy on high-value projects that actually grow the business.

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Reskill’s Service Commitment

Full Preparatory Support

We provide comprehensive support before, during, and after the training session to ensure a seamless experience for our clients. Training materials will be delivered directly to your office in advance, at no additional cost, ensuring the smooth, efficient, and enjoyable process.

Flat Rate Pricing

Guided by the principle of "Train more. Pay less," our courses are offered at a clear and fixed price with no limit on the number of participants. This approach extends even to customized, instructor-led, in-company training programs, enabling organizations to create an optimal training environment while maintaining budget clarity.

Online Training Options

To meet the diverse needs of our clients, we offer flexible training formats at no extra charge. Whether you prefer in-class sessions, online training, or a hybrid approach (partially web-based), we are here to accommodate your preferences. Please don’t hesitate to contact us to discuss the format that best suits your requirements.

Training Code: 100726 Information updated: 2026/05/11

Training Participants Who Benefits the Most Training Outcomes 3 Features Training Curriculum Training Duration Training Cost Requirements

AI Fundamentals Training [Understanding Machine Learning & Deep Learning] Goals

Participants will deepen their understanding of AI as a whole and the core learning methods that underpin it, and develop the ability to think about how to apply AI within their own organization.

Who Benefits the Most

New Employee Young employees Experienced employees Managers Engineers Foreign employees Sales people Full time employees

The following is a general list of target participants for the training and can be adjusted upon review. Please contact us regarding your needs.

Teams looking to scale productivity through AI and harness big data to drive smarter and faster decision-making.

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Result of AI Fundamentals Training [Understanding Machine Learning & Deep Learning]

Develop a foundational understanding of AI as a whole
Understand how the core technologies behind AI work
Build the ability to think about how to apply AI within their own organization

Training Objectives

1. Develop a foundational understanding of AI as a whole

Participants will explore the overall landscape of AI, covering its core concepts, historical development, and current trajectory. By gaining a broad overview, they will become equipped to follow and understand discussions related to AI.

2. Understanding how the core technologies behind AI work

Participants will take a deep dive into machine learning and deep learning, the core technologies driving AI today. By understanding how the learning process works, they will gain a clear sense of what AI is capable of.

3. Build the ability to think about how to apply AI within their own organization

Working in groups, participants will explore how AI technology could be applied to their own work, internal systems, and the products or services their company handles. By working through these questions during the training itself, participants will develop the ability to identify practical AI applications that can contribute to their company's growth.

Estimated Training Duration

7 hours (subject to change)

AI Fundamentals Training [Understanding Machine Learning & Deep Learning] Curriculum

Other training content can be incorporated into the curriculum upon request at no additional charge.

1. Fundamentals of AI	[Goal] Understand the overall landscape of AI
1. Fundamentals of AI	Ice-breaker: Think of AI examples from everyday life Definition of AI: What is AI / Strong AI vs. Weak AI History of AI: First AI Boom (late 1950s–1960s) / Second AI Boom (1980s–1990s) / Third AI Boom (2000s–present) Overview of AI Technology Core Technologies: Bayesian Statistics / Machine Learning / Deep Learning / Generative AI Programming Languages and Frameworks for AI Activity: The difference between IT and AI
2. Machine Learning	[Goal] Understand the principles and various methods of machine learning
2. Machine Learning	What is Machine Learning: What machine learning can do / Before machine learning / The evolution of data-driven learning Problems Machine Learning Addresses: Regression / Classification 3 Types of Learning: Supervised Learning / Unsupervised Learning / Reinforcement Learning How Machine Learning Works: Basics of machine learning / Rental pricing for homestays / Regression / Feature variables The Importance of Data and How to Handle It: Importance of data volume / Data formatting / Test data/Types of Algorithms: K-Nearest Neighbors / Decision Trees / Support Vector Machines Machine Learning Examples: Selecting high-probability leads / Sales forecasting Activity: Where machine learning can be applied
3. Deep Learning	[Goal] Understand the principles and characteristics of deep learning
3. Deep Learning	What is Deep Learning: What deep learning is / Features and capabilities of deep learning Neural Networks: What is a neural network / Perceptrons Layered Neural Networks: Neural networks / Enabling complex computations How Deep Learning Works: Deep neural networks / Forward propagation / Backpropagation Activity: Try forward propagation Classification Output Data: Output overview / Probability distribution Transfer Learning: What is transfer learning / Benefits of transfer learning / What does it enable? / Implementation overview
4. Natural Language Processing and Image Recognition	[Goal] Understand the basics of natural language processing and image recognition
4. Natural Language Processing and Image Recognition	Input Data for Deep Learning: Converting all electronic data into numbers for processing / Applications to NLP and image recognition Natural Language Processing: What is natural language / Natural language input / Algorithms / Use cases for NLP Image Recognition: What is image recognition / Input data / Convolutional Neural Networks (CNN) / Output results / Learning process / Use cases for image recognition Activity: Where deep learning can be applied Deep Learning Use Cases: Sentiment analysis via surveys / Product defect detection
5. Generative AI (GAI)	[Goal] Understand the basics of generative AI and how to apply it
5. Generative AI (GAI)	What is Generative AI (GAI): Using deep learning to create new content Text Generation AI: How it works: Predicting the next most probable word / How text generation AI learns Real-World Examples of Text Generation AI: ChatGPT / Key learning points / Usage information points Image Generation AI: How image generation AI learns / Generative Adversarial Networks Real-World Examples of Image Generation AI: Adding and subtracting image information [DALL-E; Nano Banana] Cautions When Using Generative AI: Probabilistic generation / Cautions regarding use cases
6. Thinking About AI Application in Your Organization	[Goal] Consider how to apply AI within your own organization
6. Thinking About AI Application in Your Organization	Cautions for Business Use of AI: Probability-based premise / Use IT when 100% accuracy is required Data Collection: The mindset of collecting data just in case / Sites that leverage big data / Internal data Activity: Think about how to apply AI in your organization: Identifying current challenges / Defining the problem / Solidifying specific AI ideas

Training Cost

We offer comprehensive customizable training programs for your entire team at a fixed rate, regardless of the number of participants. Whether you need in-class, online, or hybrid training, we can accommodate your specific needs without additional charges. Our pricing model ensures transparency and flexibility, allowing for last-minute adjustments without extra costs.

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AI Fundamentals Training [Understanding Machine Learning & Deep Learning] Participant Requirements

This session is open to all skill levels

Area

We offer a variety of instructor-led training programs in Singapore, both online and in-person.

Frequently Asked Questions

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Does the AI Fundamentals Training [Understanding Machine Learning & Deep Learning]course include practical content?: Yes. The course is designed to meet the needs of our clients and teach skills that can be put into practice right away.

Is the AI Fundamentals Training [Understanding Machine Learning & Deep Learning] course available online?: Online and partially web-based courses are both available upon request.

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