Dec '25 (edited) • General discussion
School of AI Courses & Bootcamps (Located on the Top 2nd Tab)
At School of AI Classroom - We are working on putting some high-quality content out for you, which you can find in the Classroom tab above.
We have around 15 courses that we are working on to have them completely available for you. I have added the details here on what will be available here:
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1 - AI Engineer Bootcamp - FREE 7-day self-paced Bootcamp
Day 1 – AI Engineering Foundations & Modern AI Stack
Day 2 – Data for AI & Prompt Engineering
Day 3 – LLMs, Embeddings & Retrieval-Augmented Generation (RAG)
Day 4 – Building AI Agents & Tool Use
Day 5 – Model Deployment & AI APIs
Day 6 – AI Ops, Monitoring & Optimization
Day 7 – AI System Design + Capstone Build
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2- 5-Day Agentic AI Bootcamp (FREE)
DAY 1 — Foundations of Agentic AI
DAY 2 — Memory, Context & Reasoning
DAY 3 — Planning, Toolchains & Workflows
DAY 4 — Multi-Agent Systems & Collaboration
DAY 5 — Production, Governance & Deployment
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3 - AI Agents for Everyone - FREE Course Available right now
You can check the curriculum by just clicking on it, as it's available
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4 - MCP for Leaders: Architecting Context-Driven AI - FREE Course Available right now
You can check the curriculum by just clicking on it, as it's available
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5 - AI for Financial Leaders: Strategy, Risk & Growth - FREE Course Available right now
You can check the curriculum by just clicking on it, as it's available
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6 - Agentic AI for the Enterprise Cloud - FREE Course Available right now
You can check the curriculum by just clicking on it, as it's available
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7 - January 2026 Build 30 AI Projects in 30 Days - Unlocks at Level 3 or Premium Course
Projects will be added as and when we build, starting January 1st. We do not have a set curriculum for this at the moment.
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8 - 2-Day Bootcamp - Level 1: Applied AI Practitioner Certificate (Available January 1st)
Premium Course (Certificate will be available on completion)
DAY 1 — AI Foundations & Generative AI in Practice
DAY 2 — Applied AI, Data & Agents
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9 - AI Product Manager Explorer - Premium Course
Section 1:
Day 1: What is AI and Why It Matters for PMs
Lecture 1:
AI vs Machine Learning vs Data Science
Lecture 2:
The Evolution of AI in Product Development
Lecture 3:
Types of AI: Narrow, General, and Generative
Lecture 4:
The Role of a PM in an AI Project
Lecture 5:
The Role of a PM in an AI Project
Section 2:
Day 2: AI Use Cases and Product Opportunities
Lecture 6:
Common AI Patterns
Lecture 7:
Domain-Specific AI Applications
Lecture 8:
Identifying AI-Ready Problems
Lecture 9:
Exploring User Impact and Value
Lecture 10:
Opportunity Framing for PMs
Section 3:
Day 3: Understanding the AI Workflow
Lecture 11:
The AI Lifecycle Simplified
Lecture 12:
Who Does What in an AI Team
Lecture 13:
The Role of Data in Product Success
Lecture 14:
Why AI Product Development is Iterative
Lecture 15:
Case Exercise: Mapping an AI Workflow
Section 4:
Day 4: Framing AI Product Strategy
Lecture 16:
Understanding the Problem-Solution-Data Fit
Lecture 17:
User Needs vs Data Availability
Lecture 18:
Defining AI Goals and Success Criteria
Lecture 19:
Aligning Product Vision with AI Capabilities
Lecture 20:
Case Study: Framing a Use Case
Section 5:
Day 5: Managing AI Teams
Lecture 21:
Core Roles in an AI Team
Lecture 22:
Running Agile AI Sprints
Lecture 23:
Collaborating Across Disciplines
Lecture 24:
Managing Expectations and Uncertainty
Lecture 25:
Conflict & Decision-Making in AI Teams
Section 6:
Day 6: Evaluating AI Impact
Lecture 26:
Introduction to AI Metrics
Lecture 27:
Human-in-the-Loop and Feedback
Lecture 28:
Ethical AI and Responsible Evaluation
Lecture 29:
Defining Success Beyond the Model
Lecture 30:
Communicating AI Performance
Section 7:
Day 7: Build Your AI Product Plan
Lecture 31:
Select Your Use Case
Lecture 32:
Draft Your Product Vision
Lecture 33:
Outline the Roadmap and Metrics
Lecture 34:
Create a Stakeholder Summary
Lecture 35:
Peer Review and Final Certification
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10 - 100 AI Agents in 100 Days - Premium Course
Section 1: Days 1–10: Personal Productivity Agents
Day 1: Daily task prioritization agent
Day 2: Email summarization agent
Day 3: Calendar conflict resolver agent
Day 4: Meeting agenda generator agent
Day 5: Personal knowledge base agent
Day 6: Daily goal reflection agent
Day 7: Smart reminder agent
Day 8: Note-to-action item agent
Day 9: Time-blocking planner agent
Day 10: Habit tracking agent
Section 2:Days 11–20: Writing & Content Agents
Day 11. Blog post generator agent
Day 12. LinkedIn post ideation agent
Day 13. Resume optimization agent
Day 14. Cover letter writing agent
Day 15. Grammar correction agent
Day 16. Tone rewriting agent
Day 17. SEO keyword expansion agent
Day 18. Product description agent
Day 19. FAQ generation agent
Day 20. Script-to-slide outline agent
Section 3: Days 21–30: Research & Analysis Agents
Day 21. Web research agent
Day 22. Competitive analysis agent
Day 23. Market trend summarization agent
Day 24. Academic paper explainer agent
Day 25. YouTube video summary agent
Day 26. News aggregation agent
Day 27. Survey insight extraction agent
Day 28. SWOT analysis agent
Day 29. Policy document summarizer agent
Day 30. Investment thesis generator agent
Section 4: Days 31–40: Business Operations Agents
Day 31. Invoice processing agent
Day 32. Expense categorization agent
Day 33. Customer support response agent
Day 34. CRM data enrichment agent
Day 35. Lead qualification agent
Day 36. Sales follow-up agent
Day 37. Contract clause explanation agent
Day 38. Vendor comparison agent
Day 39. Internal SOP generator agent
Day 40. KPI dashboard insight agent
Section 5: Days 41–50: Marketing & Growth Agents
Day 41. Ad copy generator agent
Day 42. Campaign performance analysis agent
Day 43. A/B test suggestion agent
Day 44. Customer persona builder agent
Day 45. Funnel optimization agent
Day 46. Email marketing agent
Day 47. Influencer outreach agent
Day 48. Product launch checklist agent
Day 49. Social media scheduling agent
Day 50. Brand voice consistency agent
Section 6: Days 51–60: Data & Automation Agents
Day 51. CSV data cleaning agent
Day 52. Spreadsheet formula generator agent
Day 53. API response interpreter agent
Day 54. Log anomaly detection agent
Day 55. Data validation agent
Day 56. Workflow orchestration agent
Day 57. ETL pipeline design agent
Day 58. Error classification agent
Day 59. Monitoring alert explanation agent
Day 60. Automation recommendation agent
Section 7: Days 61–70: AI & Engineering Agents
Day 61. Prompt optimization agent
Day 62. Model comparison agent
Day 63. RAG document retrieval agent
Day 64. Tool-calling agent
Day 65. Multi-step reasoning agent
Day 66. Code refactoring agent
Day 67. Bug explanation agent
Day 68. API documentation agent
Day 69. Test case generation agent
Day 70. System architecture explainer agent
Section 8: Days 71–80: HR, Legal & Compliance Agents
Day 71. Job description generator agent
Day 72. Candidate screening agent
Day 73. Interview question generator agent
Day 74. Performance review agent
Day 75. Policy compliance checker agent
Day 76. Risk assessment agent
Day 77. Legal clause summarization agent
Day 78. Data privacy explanation agent
Day 79. Training content generator agent
Day 80. Audit preparation agent
Section 9: Days 81–90: Finance & Decision-Making Agents
Day 81. Budget planning agent
Day 82. Cash flow forecasting agent
Day 83. Pricing strategy agent
Day 84. Cost optimization agent
Day 85. Revenue breakdown agent
Day 86. Financial report explainer agent
Day 87. Scenario analysis agent
Day 88. Investment risk agent
Day 89. Crypto market sentiment agent
Day 90. Trading strategy explanation agent
Section 10: Days 91–100: Advanced & Creative Agents
Day 91. Multi-agent collaboration system
Day 92. Autonomous decision agent
Day 93. Long-running monitoring agent
Day 94. Human-in-the-loop approval agent
Day 95. Error recovery agent
Day 96. Memory-enabled agent
Day 97. Persona-driven agent
Day 98. Self-improving agent
Day 99. Ethics & guardrails agent
Day 100. Production-ready autonomous AI agent
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11 - Level 2: Certified AI Engineer/AI Product Builder
12 - Level 3: Certified Agentic AI Architect
13 - Lvl 4: Certified AI Strategy & Transformation Lead
(DETAILS OF THESE WILL BE AVAILABLE AFTER Level 1 is complete - So before 5th January)
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14 - CAIO Leading Enterprise AI Transformation
Week 1: The Role of the Chief AI Officer
Lecture 1: What is a Chief AI Officer
Lecture 2: AI in the C-Suite — Strategic Mandate
Lecture 3: Evolution of Enterprise AI Leadership
Lecture 4: The AI Maturity Model
Lecture 5: Core Competencies of a CAIO
Lecture 6: Building an AI Vision and Charter
Lecture 7: Case Study — The First 100 Days of a CAIO
Week 2: Foundations of Artificial Intelligence
Lecture 8: AI vs ML vs Deep Learning vs Generative AI
Lecture 9: Neural Networks & Transformers Demystified
Lecture 10: Key AI Platforms (OpenAI, AWS, Google, IBM Watsonx)
Lecture 11: Data Pipelines and Feature Stores Basics
Lecture 12: AI Model Lifecycle Management
Lecture 13: From PoC to Production in AI
Lecture 14: Hands-on Demo — Simple AI Workflow Simulation
Week 3: Data Strategy and Infrastructure
Lecture 15: Data as the Fuel for AI
Lecture 16: Data Architecture for Enterprises
Lecture 17: Data Quality, Bias, and Labeling
Lecture 18: Building a Data Governance Framework
Lecture 19: Cloud & On-Prem Hybrid AI Infrastructure
Lecture 20: Edge AI and IoT Integration
Lecture 21: Case Study — Data Infrastructure at Scale
Week 4: AI Product Management and Lifecycle
Lecture 22: Framing AI Use Cases That Matter
Lecture 23: AI Feasibility vs Business Value
Lecture 24: The AI Development Lifecycle
Lecture 25: Human-in-the-Loop Design
Lecture 26: Metrics for AI Success — Beyond Accuracy
Lecture 27: AI ROI and Business Value Modeling
Lecture 28: Case Study — Building an AI Product Roadmap
Week 5: AI Governance and Compliance
Lecture 29: Why AI Governance Matters
Lecture 30: Principles of Responsible AI
Lecture 31: Explainability, Fairness, and Transparency
Lecture 32: Regulatory Frameworks (EU AI Act, NIST AI RMF)
Lecture 33: Risk Management in AI Systems
Lecture 34: Governance Tools and Platforms (IBM Watsonx Governance etc.)
Lecture 35: Ethical Dilemmas in AI Leadership
Week 6: AI Architecture and Infrastructure Strategy
Lecture 36: Designing Enterprise AI Architecture
Lecture 37: ModelOps and MLOps Foundations
Lecture 38: AI Infrastructure Stack — GPU, Containers, Kubernetes
Lecture 39: AI Pipelines and CI/CD Automation
Lecture 40: AI Performance Monitoring and Observability
Lecture 41: Scalable Deployment Patterns
Lecture 42: Case Study — Cloud-Native AI Architecture
Week 7: Generative AI and LLM Ecosystem
Lecture 43: Anatomy of Large Language Models
Lecture 44: Prompt Engineering for Leaders
Lecture 45: Fine-Tuning and Retrieval-Augmented Generation (RAG)
Lecture 46: Multi-Modal AI (Images, Speech, Video)
Lecture 47: AI Agents and Autonomous Workflows
Lecture 48: LLM Evaluation and Benchmarking
Lecture 49: Enterprise GenAI Use Cases and Risks
Week 8: AI for Business Functions
Lecture 50: AI in Marketing and Sales
Lecture 51: AI in Operations and Supply Chain
Lecture 52: AI in Finance and Risk Analytics
Lecture 53: AI in Human Resources and Talent Management
Lecture 54: AI in Customer Experience and Service
Lecture 55: AI in R&D and Innovation
Lecture 56: Designing AI Centers of Excellence (CoE)
Week 9: Change Management and AI Culture
Lecture 57: Building an AI-Ready Culture
Lecture 58: Upskilling and Reskilling Workforces
Lecture 59: Cross-Functional Collaboration Models
Lecture 60: Overcoming Resistance to AI
Lecture 61: AI Communication and Storytelling for Executives
Lecture 62: Leading with Empathy in AI Transformation
Lecture 63: Case Study — Cultural Change in AI Adoption
Week 10: Financial and Strategic Planning for AI
Lecture 64: AI Budgeting and Investment Models
Lecture 65: Build vs Buy vs Partner Decisions
Lecture 66: Vendor and Ecosystem Management
Lecture 67: AI KPIs and OKRs for Enterprises
Lecture 68: Strategic Portfolio Management
Lecture 69: Forecasting AI Impact on Revenue and Costs
Lecture 70: Case Study — AI ROI Dashboard
Week 11: AI Security and Risk Management
Lecture 71: AI Threat Landscape and Attack Vectors
Lecture 72: Adversarial AI and Model Poisoning
Lecture 73: Data Privacy and Protection in AI
Lecture 74: Secure AI Development Lifecycle
Lecture 75: Compliance with Security Standards (ISO, SOC, NIST)
Lecture 76: AI Incident Response and Mitigation Plans
Lecture 77: Case Study — AI Security Breach Analysis
Week 12: The Future of AI Leadership and Capstone
Lecture 78: The Next Frontier of AI Innovation
Lecture 79: AI and Sustainability Initiatives
Lecture 80: Quantum Computing and AI Integration
Lecture 81: Future of Work with AI Agents
Lecture 82: The CAIO Playbook — Final Strategy Plan
Lecture 83: Capstone Project Presentation & Feedback
Lecture 84: Graduation and Next Steps as a CAIO
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15 - Brain-Computer Interfaces & Neurotechnology
Section 1: Introduction to Brain-Computer Interfaces
Lecture 1: What Are BCIs and Why They Matter
Lecture 2: Historical Evolution of Neurotechnology
Lecture 3: The Brain-Machine Paradigm: Human-AI Integration
Lecture 4: Applications Across Healthcare, Defense, Gaming, and Accessibility
Lecture 5: Overview of BCI Categories (Invasive, Non-Invasive, Hybrid)
Lecture 6: Lab 1 – Build Your First Brain-Signal Recorder (EEG Streaming Test)
Section 2: The Human Brain and Neural Communication
Lecture 7: Fundamentals of Neuroanatomy and Neurons
Lecture 8: Action Potentials and Synaptic Transmission
Lecture 9: Neural Oscillations and Brain Rhythms
Lecture 10: Brain Regions for Motor Control, Vision, and Cognition
Lecture 11: Measuring Brain Activity (EEG, fMRI, MEG, ECoG)
Lecture 12: Lab 2 – Measure Your Alpha, Beta, and Theta Brain Waves
Section 3: Neural Signal Acquisition & Hardware
Lecture 13: EEG, ECoG, and Implantable Electrodes
Lecture 14: Sensors, Amplifiers, and Noise Reduction
Lecture 15: Sampling, Filtering, and Signal Conditioning
Lecture 16: Wearable BCIs and Consumer Neurotech Devices
Lecture 17: Emerging Interfaces (Optical, fNIRS, Ultrasound, Nano-BCIs)
Lecture 18: Lab 3 – Build an EEG Filtering & Noise-Reduction Pipeline
Section 4: Signal Processing for BCIs
Lecture 19: Time, Frequency, and Time-Frequency Analysis
Lecture 20: Feature Extraction (P300, SSVEP, ERD/ERS)
Lecture 21: Artifact Removal (Eye Blinks, Muscle Noise)
Lecture 22: Dimensionality Reduction (PCA, ICA)
Lecture 23: Real-Time Processing Pipelines
Lecture 24: Lab 4 – Extract P300 and SSVEP Features from Simple Visual Stimuli
Section 5: Machine Learning for Neural Decoding
Lecture 25: From Features to Intent: Pattern Recognition in BCIs
Lecture 26: Supervised and Unsupervised Learning for Neural Data
Lecture 27: Deep Learning Architectures for Signal Decoding
Lecture 28: Transfer Learning and Adaptive BCIs
Lecture 29: Evaluation Metrics and Cross-Validation
Lecture 30: Lab 5 – Train a Machine-Learning Classifier for Brain Signals
Section 6: Brain Stimulation and Feedback Systems
Lecture 31: Closed-Loop BCIs and Feedback Mechanisms
Lecture 32: Neurostimulation (tDCS, TMS, DBS)
Lecture 33: Haptic, Auditory, and Visual Feedback in BCIs
Lecture 34: Adaptive Control and Reinforcement Learning
Lecture 35: Cognitive State Monitoring
Lecture 36: Lab 6 – Build a Real-Time Neurofeedback System (Closed-Loop BCI)
Section 7: Applications of BCIs and Neurotechnology
Lecture 37: BCIs in Medicine: Prosthetics, Stroke Rehab, Epilepsy
Lecture 38: Communication BCIs for Locked-In Patients
Lecture 39: BCIs in Gaming, AR/VR, and Human Enhancement
Lecture 40: Brain-Controlled Robotics and Drones
Lecture 41: BCIs in Mental Health and Cognitive Training
Lecture 42: Lab 7 – Control a Device Using Your Brain (LED, Keyboard, or Cursor Control)
Section 8: Software, Tools, and Frameworks
Lecture 43: EEG/BCI Software: OpenBCI, BrainFlow, EEGLAB, MNE-Python
Lecture 44: BCI APIs and SDKs (Emotiv, NeuroSky, Neurable)
Lecture 45: Signal Simulation and Visualization
Lecture 46: Real-Time Processing with Python and MATLAB
Lecture 47: Building Custom Pipelines with Open Source Tools
Lecture 48: Lab 8 – Hands-On With BCI Frameworks & SDKs
Section 9: Neuroethics, Security, and Society
Lecture 49: Neuroethics: Privacy, Consent, and Cognitive Liberty
Lecture 50: NeuroRights and Brain Data Protection
Lecture 51: Dual-Use Dilemmas: Enhancement vs Manipulation
Lecture 52: Societal and Legal Implications of Thought Interfaces
Lecture 53: Policy and Governance in the Neurotech Era
Lecture 54: Lab 9 – Neuroethics, Security, and Cognitive Privacy
Section 10: Capstone Project and Future of BCIs
Lecture 55: Build a Simple EEG-Based Control Interface (e.g., blinking LED or cursor)
Lecture 56: Classify Mental States Using Real EEG Data
Lecture 57: Design a Neurofeedback System Prototype
Lecture 58: Draft a Whitepaper on a Future Neuro-AI Innovation
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16 - 1000 Days of AI Projects
Day 80 has been completed - and we will be adding the rest of the Projects by 15th January.
All the 1000 Projects are completed and ready - Only editing to add to the Course is left
You can find the list here - https://gist.github.com/vivianaranha/d92420632dd15834501e907e1b0c6a74
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17 - AI Engineer Bootcamp - FREE 7-day self-paced Bootcamp (Starting January 18th)
18 - AI Engineer Bootcamp - FREE 7-day self-paced Bootcamp (Starting February 1st)
Curriculum same as 1 (Starting January 4th)
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We are planning to have all these available ASAP - and we are working on a few more courses as and when there is a request from the community.
By the end of 2026, we are planning to have multiple (around 100) courses and bootcamps available to its members.
Stay Tuned, and if you have any requests, do let me know....
Premium Membership is currently at 1$/ Month or $10/year - we will be changing it back to the usual 9$/Month and $100$/year on Feb 1st. (All the resources are free but this helps us pay for the platform, tools and the SME we invite)
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School of AI Courses & Bootcamps (Located on the Top 2nd Tab)
skool.com/school-of-ai
School of AI WhatsApp Channel: https://chat.whatsapp.com/JuqbToSN6bcJAY94jLzZEd
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