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Online and partially web-based courses are both available upon request.

Corporate Training Home > Job-Based Training > Information Technology Training > AI Training > AI Fundamentals Training [Understanding Machine Learning & Deep Learning]

AI Fundamentals Training [Understanding Machine Learning & Deep Learning]

Acquire standard techniques and basic skills for practical, immediate AI application in daily work.

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: 2026/07/14

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

AI Fundamentals Training 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

Develop a proper understanding of AI characteristics and limitations to make appropriate decisions during business use.
Leverage the C.R.E.A.T.E. framework to draw out high-precision outputs directly applicable to daily work.
Avoid data leakage risks and AI biases, allowing participants to build their own safe operational rules.

Training Objectives

1. Systematically understand the mechanisms and limitations of Generative AI (LLMs) to establish a clear picture of practical utilization

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. Master the skills to output highly practical text on the first try by utilizing the C.R.E.A.T.E framework and adding negative constraints.

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. Accurately evaluate and avoid risks related to data leakage and factual errors (hallucinations) to create a safe AI playbook.

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 Curriculum

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

1. AI Overview	[Goal] Understand how AI works and their limitations.
1. AI Overview	Icebreaker: Two Truths and a Hallucination History of AI (Late 1950's - Present) Large Language Models (LLMs): What Is It, Data Training Phase, Static vs Real-Time Access Mechanics of Text Prediction: Understanding Tokens, Probability and Vector Spaces Context Windows and Memory Activity: The "Human AI" Simulation
2. Art of the Prompt	[Goal] Learn how to incorporate effective prompting to maximize the capabilities of AI.
2. Art of the Prompt	Activity: How Do We Fix It? Shift from Search Engine to Assistant: Search vs Prompt Mindset, Brevity is Not Best, Collaboration Boundary C.R.E.A.T.E. Framework: What It Is and Examples Reference: C.R.E.A.T.E. Examples Control Tone and Style: Move Beyond Generic Adjectives, Negative Constraints Managing Constraints and Output Formats: Define Structural Enclosures, Word and Token Ceilings Activity: Prompt Makeover
3. Advanced Prompting & Workflows	[Goal] Review advanced prompting techniques.
3. Advanced Prompting & Workflows	Multi-Turn Conversations: Shatter the "One-Shot" Habit, Manage Conversational Drift Zero-Shot vs Few-Shot Prompting: Definition, Balance Variety of Samples Chain-of-Thought (CoT) Engineering: Force Internal Monologue, Scripted CoT Workflows Adding Information and Documents: Document Grounding, Manage Source Citations, Large Data Sets Persona Integration and Roleplay: Behavioral Subnets, Adversarial Stakeholders, Multi-Persona Panels Feedback Loops: Author to Editor, Structured Critique Loop, Quality Gates Activity: Persona Sandbox
4. Data Privacy, Bias, & Ethics	[Goal] Develop awareness around how data privacy, bias, and ethics must be considered when using AI.
4. Data Privacy, Bias, & Ethics	Public Bulletin Board The Lifecycle of Prompt Data: Ingestion vs Storage, Training Feedback Loop, Opt-Out Mechanisms Corporate Data Leaks: Accidental Intellectual Property Ingestion, Personally Identifiable Information (PII) Violations, Enterprise Solutions vs Consumer Tools Algorithmic Bias: "Garbage In, Garbage Out" Reality, Historical Disparities in Text Representation, Hallucinations, False Citations Ethics of Synthetic Media Generation: Synthetic Disinformation Mitigate Risks with Prompt Alignment: Design Explicit Safety Boundaries, Neutralize Bias with Representation Rules Activity: AI Audit
5. AI as a Collaborative Partner	[Goal] Grasp additional functionalities of AI as a collaborative partner.
5. AI as a Collaborative Partner	Activity: The Tone Telephone Brainstorming Partner: Overcoming "Blank Page" Syndrome, Lateral Thinking Structural Outlining: Deconstructing Long-Form Documents, Reverse-Engineering Successful Layouts, Balance Information Density Across Sections Precision Tone Shifting and Channel Tuning: Isolate Stylistic Vectors, Vocabulary Exclusion, Adapting Content for Platform-Specific Formats Cultural Translation and Localization Adjustments: Move Beyond Literal Translation, Calibrate Directness and Politeness, Using Humor, Idioms and Metaphors Maintaining the Unique Human Voice: Feed AI Your Personal Style Samples, 70/30 Rule, Use Personal Anecdotes and Authentic Data Collaborative Editing Loop: Treat AI as a Draft, Post-Draft Linguistic Audit Activity: Transforming Notes
6. Multimodal AI & Automation	[Goal] Gain additional skills to use AI beyond text functions.
6. Multimodal AI & Automation	Activity: The Sketch Artist The Landscape of Multimodal AI: Defining Modality, Native Multimodal Models vs Segmented Pipelines Generative Image Engines: Transform Abstract Ideas, Visual Modifiers and Style Overlays, Iterative Inpainting and Aspect Ratio Control Data Analysis: Sandboxed Code Execution, Data Cleaning and Preprocessing, Statistics and Trend Spotting Automated Voice Workflows and Transcription: Audio Parsing and Transcription, Speaker Diarization, Conversational Brain Dumps Multi-Modal AI Tool Chains: Sequential Chaining Architectures, Mitigate Compounding Errors Across Chains, Cross-Modal Feedback Loops
7. Build Your AI Playbook	[Goal] Identify and create a workflow to integrate AI into daily work.
7. Build Your AI Playbook	Activity: Implement AI Into Your Work (Brainstorm, Pick Your Target, Write Your Prompt, Present)

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 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

I would like to know how much the AI Fundamentals Training course cost.: Click here to get a quotation in 10 seconds.

Does the AI Fundamentals Trainingcourse 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.