Your first year is where it all begins. Before building models or writing algorithms, you need to understand what data science actually is — and learn to see the world through data. In Year 1, you’ll develop the mindset and core skills that every great data scientist carries: the ability to ask the right questions, explore messy data with confidence, and turn raw numbers into stories that drive decisions.

By the end of Year 1, you’ll be comfortable working with real datasets, creating compelling visualizations, and communicating insights to audiences who don’t speak “data.”

What You’ll Be Able to Do

Frame a data science problem and map out a solution approach

Explore, clean, and understand datasets using Python

Identify patterns, distributions, and relationships in data

Build visualizations that reveal insights — not just display numbers

Tell a data story that connects analysis to real-world impact

Data Science Courses

Course What You’ll Learn Key Skills
Introduction to Data Science Understand the data science landscape, how projects are structured, and how data science creates value across industries — from healthcare to finance to e-commerce. Problem framing, data science methodology, use-case evaluation
Data Mining and Visualization Dive into real datasets through Exploratory Data Analysis (EDA). Learn to handle missing values, detect outliers, understand distributions, and build visualizations that communicate findings clearly. Python (pandas, seaborn, Bokeh), EDA, data quality assessment, feature discovery, visual storytelling

Beyond the Data Science Courses

Year 1 also builds the mathematical and computational foundations you’ll rely on throughout the program — discrete mathematics, calculus, algorithm design, and programming fundamentals. These aren’t separate from data science; they’re the language it’s written in.

Year 1 is where curiosity meets structure. You’ll finish it ready to move from “what is data science?” to “let me build something with it.”