Modular approach to NSS learning experience

NSS_MODULAR.md

Modular Curriculum for Software Development with AI

Module Code Key

• F - Foundation Modules: Core programming and web development fundamentals
• AI - AI Fundamentals: Introduction to AI concepts and capabilities
• B - Backend Development: Server-side programming and data management
• D - DevOps and CI/CD: Infrastructure, deployment, and operational excellence
• E - Enhancement Modules: Integrating AI into existing applications
• S - Specialization Modules: Advanced topics for specific career paths
• C - Capstone Projects: Applied learning through comprehensive projects

Level Indicators

• Beginner (B): No prior experience required
• Intermediate (I): Some programming experience needed
• Advanced (A): Significant development experience required
• Mixed levels (B/I or I/A): Bridging levels with aspects of both

Foundation Modules

Module Code	Module Name	Level	Duration	Description	Key Topics	Hands-On Deliverables
F1	Web Development Fundamentals	B	3 weeks	Core web technologies and standards	HTML5, CSS3, JavaScript basics, DOM manipulation, web accessibility	Build a responsive portfolio website, Create accessible web forms, Implement interactive UI elements
F2	Modern Frontend Development	I	3 weeks	Component-based web development	React, component architecture, state management, frontend testing	Build a React application with multiple components, Implement state management, Write unit tests for components
F3	Software Development Practices	B/I	2 weeks	Professional development workflows	Git, GitHub, testing fundamentals, documentation, Agile methodologies	Create a GitHub repository with proper branching, Write technical documentation, Participate in Agile sprint simulation
F4	Data Structures and Algorithms	I	3 weeks	Computational thinking and problem solving	Arrays, linked lists, trees, graphs, algorithm analysis, optimization	Implement common data structures, Solve algorithm challenges, Analyze and optimize code performance
F5	TypeScript and Advanced JavaScript	I/A	2 weeks	Modern JavaScript development	TypeScript, advanced patterns, performance optimization, module systems	Convert JavaScript project to TypeScript, Implement design patterns, Create modular code architecture

AI Fundamentals

Module Code	Module Name	Level	Duration	Description	Key Topics	Hands-On Deliverables
AI1	Introduction to AI and ML	B	1 week	Conceptual foundations of AI	AI/ML/LLM concepts, capabilities and limitations (hallucinations, context limits), ethics, prompt engineering, major model types (GPT, Claude, LLaMA, Mistral)	Create a simple Q&A bot with OpenAI API, Experiment with different prompts and roles, Analyze AI limitations through practical examples
AI2	Foundation Models and Applications	B/I	2 weeks	Understanding modern AI models	Foundation models, text/image/multimodal AI, application patterns, output evaluation, non-chat applications (search, summarization, classification, extraction)	Build a multi-turn chat app with history, Implement a document summarizer, Create a simple content classifier
AI3	HuggingFace Ecosystem	I	2 weeks	Using the HuggingFace platform	Hub navigation, pre-trained models, model selection, Spaces, model deployment, dataset management	Deploy a pre-trained model on HuggingFace Spaces, Fine-tune a model on a custom dataset, Create a demo application
AI4	Practical Machine Learning	I/A	3 weeks	ML concepts for developers	ML fundamentals, training vs. inference, embeddings, vector databases, semantic search, chunking and indexing	Generate embeddings for custom data, Build a semantic search system, Store and query data in a vector database
AI5	AI Evaluation and Testing	I/A	2 weeks	Quality assurance for AI systems	Benchmarking, testing methodologies, bias detection, performance monitoring, RLHF (Reinforcement Learning from Human Feedback), structured evaluation frameworks	Fine-tune a model on a small dataset, Implement comprehensive evaluation metrics, Create a bias detection system, Simulate RLHF with feedback collection

Backend Development

Module Code	Module Name	Level	Duration	Description	Key Topics	Hands-On Deliverables
B1	Python Programming Fundamentals	B	2 weeks	Core Python development	Python syntax, control structures, functions, data handling, packages	Build command-line utilities, Create data processing scripts, Implement object-oriented designs
B2	Database Design and Development	B	2 weeks	Data persistence and management	Relational databases, SQL, ORM, Django models, optimization	Design a database schema, Write complex SQL queries, Implement Django models with relationships
B3	Server-Side Web Development	B	3 weeks	Building web application backends	Django framework, MVC/MTV architecture, routing, views, templates	Build a complete Django web application, Implement authentication and authorization, Create dynamic templates
B4	API Development	I	2 weeks	Creating and consuming web APIs	REST design, authentication, Django REST Framework, documentation	Build a RESTful API with Django REST Framework, Implement JWT authentication, Create API documentation with Swagger
B5	Advanced Django	A	2 weeks	Professional Django development	Signals, middleware, custom commands, channels, scalability	Implement real-time features with Django Channels, Create custom middleware, Build scalable Django applications

DevOps and CI/CD

Module Code	Module Name	Level	Duration	Description	Key Topics	Hands-On Deliverables
D1	DevOps Fundamentals	I	2 weeks	Introduction to DevOps practices	DevOps principles, CI/CD concepts, automation, monitoring basics, version control workflows	Set up a basic CI pipeline, Implement automated testing, Create monitoring dashboards
D2	Cloud Infrastructure	I	2 weeks	Cloud platform fundamentals	AWS/Azure fundamentals, IaaS vs PaaS, cloud security, cost management	Deploy applications to cloud platforms, Configure cloud services, Implement cloud security best practices
D3	Container Orchestration	I/A	2 weeks	Managing containerized applications	Docker, container registries, microservices architecture, container networking	Containerize applications, Implement multi-container deployments, Configure service discovery
D4	Infrastructure as Code	I/A	2 weeks	Automated infrastructure provisioning	Terraform, CloudFormation, configuration management, immutable infrastructure	Create infrastructure templates, Implement multi-environment deployments, Manage state and dependencies
D5	CI/CD Pipeline Design	A	2 weeks	Advanced deployment automation	Pipeline design patterns, deployment strategies, quality gates, security scanning	Design comprehensive CI/CD pipelines, Implement blue/green deployments, Integrate security scanning
D6	Site Reliability Engineering	A	2 weeks	Maintaining production systems	SLIs/SLOs/SLAs, incident management, chaos engineering, observability	Implement observability solutions, Create incident response playbooks, Design resilient systems

AI Enhancement

Module Code	Module Name	Level	Duration	Description	Key Topics	Hands-On Deliverables
E1	AI-Enhanced Search Systems	I	2 weeks	Building intelligent search	Vector databases, embeddings, hybrid search, search UI, relevance tuning	Build a semantic search engine, Implement hybrid search with keywords and vectors, Create an intuitive search interface with relevance feedback
E2	LangChain Fundamentals	I	2 weeks	LLM application framework	LangChain architecture, chains, document processing, prompting, memory management	Implement a simple LangChain chain, Add memory for multi-turn conversations, Process and analyze documents with LangChain
E3	RAG Implementation	I/A	2 weeks	Retrieval-augmented generation	RAG concepts, document pipelines, context optimization, response generation, chunking strategies	Build a complete RAG system, Optimize document chunking for retrieval, Implement context window management, Create a document Q&A system
E4	LangChain Agents	A	2 weeks	Creating autonomous AI tools	Agent architecture, tool integration, ReAct pattern, orchestration, error handling	Build an agent with multiple tools (calculator, search, API access), Implement planning loops, Create error recovery mechanisms
E5	AI Feature Integration	I/A	2 weeks	Adding AI to existing applications	Enhancement opportunities, integration patterns, optimization, UX design for AI uncertainty, security considerations, cost control	Add AI features to an existing application, Implement confidence indicators and fallbacks, Create monitoring and logging systems, Optimize token usage
E6	Multi-Agent Collaboration & MCP	A	2 weeks	Standardized AI connectivity and multi-agent systems	MCP architecture, building servers, client integration, security, agent roles (coordinator, specialists, evaluators), message passing, collaborative workflows	Build a multi-agent system with specialized roles, Implement a Model Context Protocol server, Create agent communication patterns, Design collaborative AI workflows

Specialization

Module Code	Module Name	Level	Duration	Description	Key Topics	Hands-On Deliverables
S1	AI-Enhanced Data Engineering	A	3 weeks	Large-scale data processing	ETL pipelines, data processing, vector databases, AI transformations	Build data processing pipelines with AI components, Implement vector database solutions, Create scalable ETL workflows
S2	Enterprise AI Integration	A	3 weeks	AI in large organizations	Enterprise architecture, security, multi-model systems, ROI monitoring	Design enterprise AI architecture, Implement security protocols for AI systems, Create ROI monitoring dashboards
S3	Advanced LLM Applications	A	3 weeks	Pushing LLM capabilities	Custom LLM development, fine-tuning, advanced prompting, evaluation, RLHF	Fine-tune models for specific domains, Implement advanced prompting techniques, Create comprehensive evaluation frameworks
S4	AI Product Development	I/A	3 weeks	Creating AI-first products	AI design principles, user research, UX patterns for uncertain AI, metrics, cost optimization	Design and prototype an AI-first product, Conduct user research for AI features, Implement UX patterns for handling AI uncertainty

Capstone Projects

Module Code	Module Name	Level	Duration	Description	Key Topics	Hands-On Deliverables
C1	Individual Enhancement Project	I	3 weeks	Solo AI application	Enhancing existing applications, end-to-end implementation, documentation, non-chat AI features	Develop a complete AI-enhanced application, Create comprehensive documentation, Implement monitoring and evaluation metrics
C2	Team-Based Enterprise Project	A	4 weeks	Collaborative business solution	Industry partnerships, complex business problems, full development lifecycle, enterprise integration	Build an enterprise-grade AI solution in a team, Present to industry partners, Create deployment and maintenance documentation
C3	Open Source Contribution	I/A	3 weeks	Community contribution	LangChain, HuggingFace, open source community, real-world issues	Contribute to an open source AI project, Address real-world issues, Collaborate with the community through pull requests

Sample Learning Paths

Beginner Full-Stack Path (6 months)

Phase	Module Codes	Module Names	Duration
1	F1, F3, B1	Web Development Fundamentals, Software Development Practices, Python Programming Fundamentals	7 weeks
2	F2, B2, B3	Modern Frontend Development, Server-Side Web Development, Database Design and Development	8 weeks
3	AI1, AI2, AI3	Introduction to AI and ML, Foundation Models and Applications, HuggingFace Ecosystem	5 weeks
4	E1, E2, C1	AI-Enhanced Search Systems, LangChain Fundamentals, Individual Enhancement Project	7 weeks
Total	12 modules		27 weeks

Experienced Developer AI Enhancement Path (4 months)

Phase	Module Codes	Module Names	Duration
1	AI2, AI3, AI4	Foundation Models and Applications, HuggingFace Ecosystem, Practical Machine Learning	7 weeks
2	B5, E2, E3	Advanced Django, LangChain Fundamentals, RAG Implementation	6 weeks
3	E4, E6, S2	LangChain Agents, Model Context Protocol, Enterprise AI Integration	7 weeks
4	C2	Team-Based Enterprise Project	4 weeks
Total	10 modules		24 weeks

Data-Focused AI Path (5 months)

Phase	Module Codes	Module Names	Duration
1	B1, AI1, B3	Python Programming Fundamentals, Introduction to AI and ML, Database Design and Development	5 weeks
2	AI3, AI4, E1	HuggingFace Ecosystem, Practical Machine Learning, AI-Enhanced Search Systems	7 weeks
3	E3, S1, AI5	RAG Implementation, AI-Enhanced Data Engineering, AI Evaluation and Testing	7 weeks
4	E6, C1	Model Context Protocol, Individual Enhancement Project	5 weeks
Total	11 modules		24 weeks

DevOps with AI Path (6 months)

Phase	Module Codes	Module Names	Duration
1	F3, AI2, B4	Software Development Practices, Foundation Models and Applications, API Development	6 weeks
2	E2, D1, D2	LangChain Fundamentals, DevOps Fundamentals, Cloud Infrastructure	6 weeks
3	D3, D4, E5	Container Orchestration, Infrastructure as Code, AI Feature Integration	6 weeks
4	E6, S2, C2	Model Context Protocol, Enterprise AI Integration, Team-Based Enterprise Project	9 weeks
Total	12 modules		27 weeks

AI Product Developer Path (5 months)

Phase	Module Codes	Module Names	Duration
1	F2, AI1, AI2	Modern Frontend Development, Introduction to AI and ML, Foundation Models and Applications	6 weeks
2	B4, E1, E2	API Development, AI-Enhanced Search Systems, LangChain Fundamentals	6 weeks
3	E5, S4, AI5	AI Feature Integration, AI Product Development, AI Evaluation and Testing	7 weeks
4	E6, C1	Multi-Agent Collaboration & MCP, Individual Enhancement Project	5 weeks
Total	11 modules		24 weeks

Required Resources by Module Level

Resource Type	Beginner Modules	Intermediate Modules	Advanced Modules
Instructor:Student Ratio	1:15	1:20	1:25
Lab Equipment	Basic laptop/desktop	Enhanced computing resources	Cloud computing access, GPU resources
Software	Standard development tools	Specialized frameworks	Enterprise-grade tools, API credits
Support	Regular office hours, detailed guides	Weekly mentoring	Industry mentors, on-demand support
Assessment	Structured assignments, quizzes	Projects, code reviews	Complex system design, industry evaluation