Data Science Courses
Data science combines core skills like Python, SQL, statistics, machine learning, and visualization to help you solve real problems with data. These data science courses teach foundational tools such as pandas, NumPy, Matplotlib, and scikit-learn through practical, beginner-friendly exercises. You’ll work with real datasets to clean data, explore patterns, and build simple models. Explore the catalog to start building the essential skills for a data-focused career.
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Explore All Data Science Courses
Data Analyst in R
Analyze, clean, and visualize data using R and SQL to perform end-to-end statistical analysis and communicate insights effectively.
Data Scientist in Python
Analyze complex datasets and build predictive models by applying statistics and machine learning to deliver end-to-end data science solutions.
Data Analyst in Python
Build end-to-end analytics skills with Python and SQL—cleaning data, visualizing insights, and delivering business answers.
Generative AI Fundamentals in Python
Build Python skills, work with LLM APIs, and automate tasks to create practical AI-powered applications.
Deep Learning in TensorFlow
Build and train neural networks with TensorFlow, from fundamentals to practical models that make real predictions.
Zero to GPT
Build and train deep learning models from scratch, including GPTs, by applying neural networks, optimization, and modern transformer techniques.
Machine Learning in Python
Train predictive models in Python, evaluate performance, and apply machine learning to real datasets for insights.
Data Visualization with Tableau
Master Tableau basics—cleaning, modeling, and building interactive dashboards that surface patterns and insights fast.
Data Literacy and Introduction to Data Analysis using Excel
Develop data literacy while using Excel to organize, analyze, and visualize information with practical, business-ready techniques.
Analyzing Data with Microsoft Power BI
Master core Power BI workflows—cleaning data, modeling relationships, and crafting interactive reports for business stakeholders.
Data Cleaning with Python
Clean, transform, and prepare messy datasets by applying core data cleaning techniques in Python to support reliable analysis.
Probability and Statistics with R
Apply probability, sampling, and hypothesis testing in R to make confident, data-driven decisions with practice projects.
Probability and Statistics with Python
Apply probability, sampling, and hypothesis testing in Python to make confident, data-driven decisions with practice projects.
APIs and Web Scraping with Python
Collect, clean, and merge data from APIs and websites using Python, requests, and BeautifulSoup for analysis.
APIs and Web Scraping with R
Collect data from APIs and websites in R, clean it, and combine sources for analysis projects.
Data Visualization with R
Create clear, compelling visual stories in R using ggplot2 while exploring distributions, comparisons, and relationships.
Data Analysis and Visualization with Python
Explore, analyze, and visualize real datasets with pandas, NumPy, and Matplotlib to communicate insights confidently.
R Basics for Data Analysis
Build foundational R programming skills to analyze data, automate workflows, and support exploratory data analysis.
Learn Data Science by Building Projects
Apply your skills to real-world scenarios with these guided projects
Analyzing COVID RNA Sequences in Python
For this project, we’ll step into the role of bioinformaticians to analyze the RNA sequences of COVID-19 variants using Python and key bioinformatics libraries.
Build a Speech Recognition and Summarization System
For this project, you’ll step into the role of a Python developer to build a speech recognition and summarization system that can automatically transcribe and summarize audio files.
Analyzing CIA Factbook Data Using SQL
For this project, we’ll step into the role of data analysts to explore the CIA World Factbook using SQL queries in Jupyter Notebook, uncovering key demographic insights about countries worldwide.
Analyzing Movie Ratings
For this project, we’ll step into the role of data analysts to scrape IMDb movie data using R, analyzing ratings and votes to identify trends and build data visualization skills.