Program Catalogue
Explore LearnerBox Programs
Select a program to view its free and premium learning tracks.
PROGRAM 1: AI Foundations
Start your AI journey with beginner-friendly AI literacy, tools, prompting, and productivity.
Free Track: AI Foundations for Everyone
- What is AI?
- History of AI
- AI vs Machine Learning vs Deep Learning
- Generative AI
- AI in everyday life
- AI myths and misconceptions
- ChatGPT
- Gemini
- Claude
- Microsoft Copilot
- Perplexity
- Choosing the right AI tool
- Prompt fundamentals
- Prompt anatomy
- Role prompting
- Few-shot prompting
- Prompt refinement
- Build your own prompt library
- Thinking with AI
- AI productivity workflows
- Research, writing, and learning
- Responsible AI use
- Looking under the AI hood
- AI for workplace productivity
Premium Track: AI Foundations & AI Creation
- Expanded AI foundations
- AI concepts and real-world applications
- AI limitations and ethical use
- Advanced prompting basics
- AI-assisted writing
- AI productivity workflows
- Variables and data types
- Conditional statements
- Loops
- Functions
- Lists, tuples, dictionaries, and sets
- Structured and unstructured data
- Databases
- NumPy
- Pandas
- Reading, cleaning, and summarizing datasets
- What is Machine Learning?
- Supervised learning
- Unsupervised learning
- Linear regression
- Decision trees
- K-Means clustering
- Large Language Models
- Tokens
- Embeddings
- Chatbots
- Content generation
- Knowledge assistants
- No-code AI development
- ChatGPT GPTs
- Claude Projects
- Streamlit basics
- Build a simple AI application
- AI ethics
- Bias
- Hallucinations
- Privacy
- Copyright
- Safe AI usage
PROGRAM 2: AI Engineer Program
Build job-ready AI engineering skills with Python, data analysis, machine learning, Generative AI, RAG, agents, APIs, and deployment.
Open AI Engineer ProgramPROGRAM 3: Enterprise AI & Agent Engineering
Design, deploy, govern, and scale enterprise-grade AI systems, AI agents, automation workflows, and intelligent business solutions.
Free Track: Enterprise AI Basics
- Evolution of NLP
- Tokens & Tokenization
- Embeddings
- Attention Mechanism
- Transformers
- LLM Architecture
- Why frameworks exist
- Agent frameworks vs orchestration frameworks
- LangChain
- Semantic Kernel
- CrewAI
- Framework comparison & selection
- AI agents
- Tool Calling
- ReAct
- LangGraph
- Memory
- Planning
- AI system architecture
- Vector databases
- Model deployment
- API gateways
- Security
- Authentication
- Responsible AI
- Governance
Premium Track: Enterprise AI & Agent Engineering
- Python
- Data processing
- Exploratory data analysis
- Data pipelines
- Regression
- Classification
- Clustering
- Ensemble learning
- Artificial Neural Networks
- Convolutional Neural Networks
- Optimization
- Transfer learning
- Embeddings
- Transformers
- LLM architecture
- Prompt engineering
- Hybrid search
- Reranking
- Query transformation
- RAG evaluation
- ChromaDB
- Pinecone
- Weaviate
- FAISS
- LangChain/LangGraph/ReAct
- State management
- Human-in-the-loop controls
- Memory systems
- Multi-agent systems
- Agentic RAG
- MCP
- Self-reflection
- Plan-and-execute
- CrewAI/AutoGen/DSPy
- Semantic Kernel
- Framework selection criteria
- Vendor lock-in
- Prompt injection
- Guardrails
- Access control
- Responsible AI
- Compliance
- FastAPI
- REST APIs
- Tool calling
- Enterprise integrations
- Git
- GitHub Actions
- Docker
- MLflow
- CI/CD
- Model serving
- Scaling
- Routing
- Load balancing
- Monitoring
- Observability (agents & models)
- Cost/latency governance
- Product strategy
- ROI analysis
- Business cases
- AI roadmaps
- AI architecture patterns
- Knowledge systems
- Enterprise search
- Agent ecosystems
- Enterprise capstone
PROGRAM 4: Statistics & Data Science
Build statistical thinking, data analysis, visualization, and evidence-based decision-making skills for AI, Machine Learning, Data Science, and Research.
Open Statistics Program
