Training & Internship Programme

// LEARN AI. BUILD REAL PROJECTS.

Industry-led AI training programmes with live internship experience. You will work on real Algonit AI products, guided by practitioners who build production-grade AI systems every day.

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4
AI Specialisations
Live
Internship Included
Real
Project Experience
Cert.
On Completion
Course 01

Data Science

Master data analysis, statistical modelling, and machine learning. Build real-world predictive models and data pipelines — the foundation of every AI-driven product.

3–4 Months
Internship Included
Certificate on Completion
Beginner–Intermediate
Module 1 — Python for Data
  • Python fundamentals & environment setup
  • NumPy — arrays, operations & broadcasting
  • Pandas — DataFrames, cleaning & wrangling
  • Data ingestion from CSV, JSON & APIs
  • Exploratory Data Analysis (EDA)
Module 2 — Statistics & Probability
  • Descriptive statistics & distributions
  • Probability theory & Bayes' theorem
  • Hypothesis testing & p-values
  • Correlation & regression foundations
  • Confidence intervals & sampling
Module 3 — Data Visualisation
  • Matplotlib — charts, subplots & customisation
  • Seaborn — statistical visualisations
  • Plotly — interactive dashboards
  • Storytelling with data
  • Business reporting & stakeholder charts
Module 4 — Machine Learning
  • Supervised learning — regression & classification
  • Unsupervised learning — clustering & PCA
  • Scikit-learn — pipelines & model selection
  • Ensemble methods — Random Forest, XGBoost
  • Model evaluation, tuning & cross-validation
Module 5 — SQL & Databases
  • SQL fundamentals — SELECT, JOIN, GROUP BY
  • Advanced queries — subqueries, CTEs, window functions
  • Database design & normalisation
  • Python + SQL integration (SQLAlchemy)
  • Querying PostgreSQL & MySQL
Module 6 — Capstone & Internship
  • End-to-end data science project
  • Work on live Algonit product data
  • Portfolio project & GitHub setup
  • Resume & interview preparation
  • Certificate of completion & placement support
Course 02

Generative AI

Build with large language models, image generation, and multimodal AI. From prompt engineering to shipping production GenAI applications using OpenAI, Gemini, and open-source models.

3–4 Months
Internship Included
Certificate on Completion
Intermediate
Module 1 — LLM Foundations
  • How LLMs work — transformers & attention
  • GPT-4, Gemini, Claude & Llama overview
  • Tokens, embeddings & context windows
  • OpenAI API & Gemini API setup
  • Hugging Face ecosystem
Module 2 — Prompt Engineering
  • Zero-shot, few-shot & chain-of-thought
  • System prompts & role design
  • Structured output & JSON mode
  • Prompt chaining & templates
  • Evaluation & iteration strategies
Module 3 — RAG Systems
  • What is RAG & when to use it
  • Vector databases — Pinecone, ChromaDB, FAISS
  • Document chunking & embedding strategies
  • Retrieval-augmented generation pipeline
  • Hybrid search & reranking
Module 4 — Fine-tuning Models
  • When to fine-tune vs. prompt engineer
  • Dataset preparation & annotation
  • OpenAI fine-tuning API
  • LoRA & QLoRA with open-source models
  • Evaluation & benchmarking
Module 5 — Multimodal & Image AI
  • Vision models — GPT-4V, Gemini Vision
  • DALL-E & Stable Diffusion
  • Image-to-text & text-to-image pipelines
  • Speech-to-text with Whisper
  • Building multimodal applications
Module 6 — Capstone & Internship
  • Build a production GenAI application
  • Contribute to a live Algonit AI product
  • API deployment & cost optimisation
  • Portfolio project & GitHub setup
  • Certificate of completion & placement support
Course 03

Agentic AI

Design and build autonomous AI agents that reason, plan, and execute complex tasks end to end. Master LangChain, LangGraph, and CrewAI to create multi-agent systems deployed in production.

4–5 Months
Internship Included
Certificate on Completion
Intermediate–Advanced
Module 1 — AI Agent Fundamentals
  • What are AI agents & how they work
  • Agent architectures — ReAct, Plan & Execute
  • Tools, actions & observations loop
  • Memory types — short-term, long-term, episodic
  • Agentic design patterns
Module 2 — LangChain
  • LangChain architecture & core concepts
  • Chains — sequential, parallel & conditional
  • Tool use & function calling
  • Document loaders & RAG with LangChain
  • Memory modules & conversation history
Module 3 — LangGraph
  • State machines & graph-based workflows
  • Nodes, edges & conditional routing
  • Building agentic loops with LangGraph
  • Human-in-the-loop checkpoints
  • Streaming & observability
Module 4 — CrewAI & Multi-Agent Systems
  • CrewAI architecture — agents, tasks & crews
  • Roles, goals & backstory design
  • Sequential vs. hierarchical process
  • AI-to-AI task delegation
  • Custom tools & external API integration
Module 5 — Production Agentic Systems
  • Error handling & agent reliability
  • Guardrails & safety controls
  • Cost tracking & token optimisation
  • Logging, monitoring & observability
  • Deploying agents to cloud
Module 6 — Capstone & Internship
  • Build a multi-agent system from scratch
  • Work on live Algonit Agentic AI products
  • Real-world agent debugging & optimisation
  • Portfolio project & GitHub setup
  • Certificate of completion & placement support
Course 04

AI Product Development

Go from idea to shipped AI product. Learn to design, build, test, and launch SaaS and AI-powered applications — covering backend, frontend, cloud deployment, and product thinking.

4–5 Months
Internship Included
Certificate on Completion
Intermediate–Advanced
Module 1 — Product Thinking for AI
  • AI product strategy & market positioning
  • User research & problem definition
  • AI product roadmapping
  • PRDs, wireframes & prototyping
  • Identifying AI use cases & feasibility
Module 2 — Backend Development
  • FastAPI & Flask for AI backends
  • REST API design & authentication
  • Database design — PostgreSQL & SQLAlchemy
  • AI model integration patterns
  • Background tasks & async processing
Module 3 — Frontend for AI Products
  • React fundamentals & component design
  • Streaming UI — chat interfaces & live output
  • State management & API calls
  • File upload, dashboards & data views
  • Responsive design & UX principles
Module 4 — Cloud Deployment
  • Docker & containerisation basics
  • Deploying to AWS / GCP / Azure
  • CI/CD pipelines & GitHub Actions
  • Environment management & secrets
  • Monitoring, logging & scaling
Module 5 — SaaS Architecture & Monetisation
  • SaaS architecture patterns
  • Multi-tenancy & user management
  • Subscription billing & payment integration
  • Usage metering & rate limiting
  • Go-to-market strategy for AI products
Module 6 — Capstone & Internship
  • Build & launch a full AI product
  • Contribute to a live Algonit product codebase
  • Code reviews & real engineering workflow
  • Portfolio & GitHub profile setup
  • Certificate of completion & placement support
Programme Benefits

// What You Get

Live Internship

Work on real Algonit AI products in production — not mock exercises.

Certificate

Industry-recognised certificate of completion from Algonit Technologies.

1:1 Mentorship

Personal guidance from AI practitioners building production systems daily.

Placement Support

Resume review, mock interviews, LinkedIn optimisation & referrals.

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// Start Your AI Career

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