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AI foundations

An Introduction to Generative AI

Explore generative AI, neural networks, language models, image generation and AI audio and video.

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Course topics

AI foundations

  • Language models
  • Image generation
  • Audio and video

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Find your fit

Is this a useful starting point?

For non-technical learners comfortable using a computer who want to explore generative-AI tools.

Starting point
Beginner
Course length
9 total hours
Lessons
73 lectures

Course by Avnish Singh, Pavan Kumar

Course last updated: 05/2026

Requirements
  • Basic Tech Savvy: Familiarity with using computers and browsing the internet.
  • Open Mindset: A willingness to explore new technologies and workflows.
  • No Programming Skills Required: This course is accessible to non-technical learners.
  • Interest in AI: A curiosity about artificial intelligence and its applications.
  • Professional Relevance: Ideal for learners aiming to integrate AI into their fields.
  • Basic Knowledge of Business Concepts: Helpful but not mandatory for business-related sections.
  • Access to a Computer: Required for trying out tools and platforms demonstrated in the course.
What is included
  • Role Play
  • 9 hours on-demand video
  • 9 articles
  • 25 downloadable resources
  • 1 practice test
  • Access on mobile
  • Certificate of completion

DoJo membership: A$250 per month per seat, excluding GST. Includes fortnightly group support and a private member community.

Explore the lessons

Course curriculum.

11 sections • 73 lectures • 8h 47m total length

Introduction to Generative AI 20266 lectures • 29min
  1. Welcome and Course Overview03:30
  2. What is Artificial Intelligence?04:49
  3. Explaining AI Concepts to a Non-Technical Executive
  4. Understanding Machine Learning Basics06:12
  5. Diagnosing a Machine Learning Failure Due to Data Issues
  6. What Makes Generative AI Different : Traditional AI vs Generative AI07:08
  7. Advising Leadership on Choosing the Right AI Model
  8. The Evolution of Generative AI06:49
  9. Presenting the Business Case for Generative AI Investments to Leadership
  10. Section 1 : Introduction to Generative AI Quiz 5 questions
  11. Section Recap: Key Concepts & Downloadable Notes00:06
Neural Networks - The Foundation7 lectures • 46min
  1. How Neural Networks Work - Part 108:55
  2. Demo - Google Teachable Machine — train Image model02:41
  3. Explaining Neural Network Basics to Non-Technical Executives
  4. How Neural Networks Work - Part 209:57
  5. Demo - TensorFlow Playground — Watch learning visually02:31
  6. Explaining Forward Propagation and Activation Functions to Assist Architecture Decisions
  7. Training Neural Networks10:09
  8. Diagnosing and Addressing Model Overfitting and Reliability Issues
  9. Understanding Model Parameters11:25
  10. Explaining Parameter Counts and Deployment Strategies for AI Models
  11. Neural Networks - The Foundation 5 questions
  12. Section Recap: Key Concepts & Downloadable Notes00:06
Large Language Models (LLMs)13 lectures • 1hr 19min
  1. Introduction to Large Language Models LLMs10:36
  2. Demo: ChatGPT — Next-word completion and text Generation02:10
  3. Transformers Architecture Explained11:53
  4. Demo: Translation EN → Spanish → Japanies01:49
  5. Demo — Transformers Visualization01:45
  6. How ChatGPT and GPT Models Work13:26
  7. Demo: Summarize a WhatsApp-style paragraph01:48
  8. Addressing Executive Concerns on LLM Hallucinations and Reliability
  9. Tokenization and Text Processing10:39
  10. Demo– Tokenizer and Token ID02:13
  11. Managing Tokenization Costs and Context Overflow in LLM Projects
  12. Embeddings and Vector Representations09:51
  13. Demo - Embedding Simulator03:06
  14. Convincing Leadership and Engineering to Implement Semantic Search with Embeddings
  15. The Generation Process09:36
  16. Balancing Creativity and Consistency in AI Text Generation
  17. Large Language Models LLMs 5 questions
  18. Section Recap: Key Concepts & Downloadable Notes00:06
AI Image Generation11 lectures • 1hr 31min
  1. Introduction to AI Image Generation11:21
  2. Demo - DALL-E Stable Diffusion — Text→Image generation – Gemini Nano banana02:53
  3. Variational Autoencoders (VAEs) Explained12:16
  4. Explaining Variational Autoencoders (VAEs) and Latent Spaces to Non-Technical Stakeholders
  5. Demo - Image Generation With AI06:53
  6. Demo - Inpainting — Remove object01:51
  7. Explaining the Evolution and Business Impacts of Modern AI Image Generation
  8. Understanding Diffusion Models13:46
  9. How Text-to-Image Generation Works14:03
  10. Prompting for Image Generation12:20
  11. Explaining Text-to-Image Prompt Sensitivity to a Cross-Functional Team
  12. GANs - An Alternative Approach12:28
  13. Explaining and Advocating for GAN Usage in Speed-Critical Applications
  14. Demo: GAN Simulator03:06
  15. Recommending Diffusion Models over GANs for Product Development
  16. Image Generation AI Quiz 5 questions
  17. Section Recap: Key Concepts & Downloadable Notes00:06
AI Audio and Video Generation10 lectures • 1hr 19min
  1. Text-to-Speech and Voice Generation14:24
  2. Demo Voice Text to Generation03:19
  3. Explaining Neural TTS to Support Business Decisions
  4. AI Music and Audio Generation13:16
  5. Demo - Generate Songs and Music04:28
  6. Calibrating Expectations for AI-Generated Music with a Creative Team
  7. AI Video Generation Technologies16:00
  8. Deepfakes and Face Synthesis13:44
  9. Demo - Use Heygen for Audio and Deepfake Video Generation02:44
  10. Advising Leadership on Ethical Use of Deepfakes in Marketing
  11. Demo - Image Generation with AI06:53
  12. Demo - Video Generation With AI04:01
  13. Audio and Video Generation Quiz 5 questions
  14. Section Recap: Key Concepts & Downloadable Notes00:06
AI Training and Fine-Tuning5 lectures • 50min
  1. The Pre-Training Process16:20
  2. Fine-Tuning Explained15:51
  3. Data Requirements and Quality15:30
  4. Demo - Small model vs Large model text response02:15
  5. Justify a Pre-Training Run for a Foundation Model
  6. Training and Fine-Tuning Quiz 5 questions
  7. Section Recap: Key Concepts & Downloadable Notes00:06
Prompt Engineering Mastery6 lectures • 1hr 6min
  1. Introduction to Prompt Engineering13:21
  2. Coaching a Non-Technical Product Manager on Writing Effective Prompts for Customer FAQs
  3. Core Prompting Techniques13:32
  4. Advanced Prompting Strategies16:57
  5. Prompt Engineering for Different Modalities17:23
  6. Demo - Bad Prompt VS Good Prompt Results and Style Prompting04:33
  7. Designing a Reliable Few-shot Prompt for Legal Clause Summarization
  8. Prompt Engineering Mastery Quiz 5 questions
  9. Section Recap: Key Concepts & Downloadable Notes00:06
AI Limitations and Challenges8 lectures • 1hr 1min
  1. AI Ethics : Hallucinations and Factual Accuracy13:40
  2. Demo - Hallucination example02:47
  3. Mitigating Hallucination Risks in AI-Generated Reports
  4. AI Ethics : Bias and Fairness Issues14:24
  5. Addressing Gender Bias in AI Hiring Assistant Outputs
  6. AI Ethics :Technical Limitations12:43
  7. AI Ethics : Ethical and Safety Concerns12:52
  8. Demo - Safety Refusal Examples02:21
  9. Demo - Bias correction Rewrite in Positive Tone02:18
  10. Deploying Generative AI Responsibly in Business Functions
  11. Limitations and Challenges 5 questions
  12. Section Recap: Key Concepts & Downloadable Notes00:06
Industry use cases for Generative AI Demos3 lectures • 9min
  1. Demo - Otter Meeting Agent - AI Notetaker, Transcription, Insights02:43
  2. Demo - Generating Email Response02:46
  3. Demo - Marketing Headline Variations for a Product Image03:28
The Future of Generative AI4 lectures • 19min
  1. The Path to Artificial General Intelligence (AGI)06:07
  2. Career Opportunities in Generative AI06:16
  3. Course Conclusion and Next Steps06:08
  4. Course Full Downloadable Resources00:07
Generative AI Practice Test0 lectures • 0min
  1. Generative AI Practice Test 100 questions

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