Nod Coding Bootcamp

Course Description:

The bootcamp is divided into three parts - Python Fundamentals, Data Analytics and Machine Learning.

In the first module you will learn the fundamentals of programming. The purpose of this module is to make you comfortable building and creating programs that can be used in a professional context.

With a solid foundation in programming, you’ll be able to deep dive into data analytics. The second module is designed to provide you with the technical and analytical skills required to thrive in the field of data analytics. Here, you will focus on cleaning, manipulating and analyzing data using the Pandas library. You will also learn to craft effective visualisations and build professional dashboards using Streamlit.

Having a strong foundation in programming and data analytics, you’ll be ready to delve into the world of Machine Learning which is the last module. Here you will learn libraries such as Sklearn, PyTorch, Tensorflow and LangChain.

Our way of teaching is practical and hands-on. Our goal is to make you proficient enough to pass a technical interview and the curriculum is shaped to mirror the skills of a great Data Analyst, Data Engineer or Data Scientist. Upon graduation, you will have acquired the hands-on programming skills to independently solve problems in a professional environment.

Subjects:
Python, SQL, BigQuery, Pandas, Matplotlib, Seaborn, Sklearn, Statistics, AB-testing, LangChain, PyTorch, Numpy, Bayesian Statistics, Streamlit, Plotly, Data Build Tool (DBT).

Subjects:
Matplotlib, A/B Testing, Python, Machine Learning, Data Analytics, SQL, Pandas

Course Description:

The bootcamp is divided into three parts - Python Fundamentals, Software Development and AI Engineering.

In the first module you will learn the fundamentals of programming. The purpose of this module is to make you proficient in building software and creating scripts that can be used in a professional context. You will also learn best practices for collaborating on software projects using git and GitHub.

With a strong programming core, we’ll move into the second module which will focus on Software Development and Backend Development. Here, you’ll learn how to build, test and deploy advanced software. You will also learn best practices for working with AI-powered coding tools to build faster.

AI Engineering is the final and biggest module in the bootcamp, taking up half of the curriculum. In this module you will master the LangChain ecosystem and deploy advanced AI-powered applications. You’ll gain hands-on skills in building AI Agents, RAG, MCPs.

Throughout the bootcamp you’ll build several projects with LangChain, LangGraph and LangSmith, both individually and in teams.

The Generative AI Bootcamp aims to give students the practical technical skills required to break into tech by landing positions such as AI Engineer, Software Developer or Backend Developer.

Subjects
Python, LangChain, LangGraph, LangSmith, Pandas, Git, GitHub, FastAPI, Streamlit, Docker, pytest, Claude Code, APIs, Huggingface, AI Agents, RAG, MCP, SQL.