Machine Learning & Agentic AI
A practical, project-led programme that takes students through the full ML workflow from understanding the problem and preparing data, through model training and evaluation, to deploying a working ML application. Students work with real datasets and finish with a deployable project.
Key Outcomes: Supervised and unsupervised learning fundamentals • Python, NumPy, Pandas, Scikit-Learn • Build, train, evaluate, and tune ML models • Deploy a machine learning model as a usable application
This bootcamp teaches you to build production-ready Agentic AI systems using Anthropic’s Claude API and Python. Rather than abstract theory, every session revolves around writing code, running agents, and shipping mini-projects. By Week 6 you will have a portfolio of real agents you can show employers.
Course TitleAgentic AI Bootcamp: Building Real-World AI Agents with Claude & Python
Duration5-6 Weeks (30+ hours of hands-on labs)
FormatLecture (30%) + Live Coding (70%)
Modules 6 Core Modules + Capstone ProjectTarget AudienceGraduate students with Python experience
Primary ToolsClaude API (claude-sonnet-4-6), Python 3.11+, LangChain, LangGraph
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Data Science with Python
Data Science sits at the intersection of statistics, programming, and business insight. This programme teaches students how to work with real data end-to-end — from loading and cleaning raw datasets, through exploratory analysis and visualisation, to building predictive models.
Key Outcomes: Pandas, NumPy, Matplotlib, Seaborn • Exploratory data analysis on real-world datasets • Build predictive models with Scikit-Learn • Create clear visualisations and communicate findings professionally
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Docker & Containerisation
SparkAI’s Docker programme takes students from zero to production-ready containerisation skills. Build, run, and manage containers. Write Dockerfiles. Work with Docker Compose, networking, and persistent storage — the way developers use it on the job.
Key Outcomes: Build and optimise containers from scratch • Docker Compose for multi-container environments • Deploy containerised applications confidently
GitHub & Version Control
Version control is non-negotiable in any software team. This programme goes beyond basic Git commands — students learn how professional teams collaborate, manage branches, resolve conflicts, and maintain clean repositories. Every student builds a live GitHub profile through the course.
Key Outcomes: Professional Git workflows • Branch management, merges, rebases, pull requests • Build a GitHub portfolio employers can review
CI/CD Pipelines
Continuous Integration and Continuous Deployment is how modern teams ship software reliably. This course teaches students to design, build, and maintain automated pipelines — integrating with GitHub, running automated tests, building Docker images, and deploying to cloud environments.
Key Outcomes: Build automated pipelines using GitHub Actions • Integrate testing into build pipelines • Connect pipelines to containerised deployments
How SparkAI Teaches
Every programme is built around hands-on from day one — no death-by-slides. Students write code, build projects, and solve real problems from the first session. The goal is a GitHub portfolio recruiters can open, not just a certificate.Running a batch for your college? | Enquire About Upcoming Batches