All Career Tracks
Learn more about the difference between R and Python
Associate Data Scientist
Learn Python for data science and gain the career-building skills you need to succeed as a data scientist, from data manipulation to machine learning! In this track, you’ll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Starting with the Python essentials for data science, you’ll work through interactive exercises that test your abilities. You’ll get hands-on with some of the most popular Python libraries for data science, including pandas, Seaborn, Matplotlib, scikit-learn, and many more. As you progress, you’ll work with real-world datasets to learn the statistical and machine learning techniques you need to perform hypothesis testing and build predictive models. You’ll also get an introduction to supervised learning with scikit-learn and apply your skills to various projects. Start this track, grow your data science skills, and begin your journey to confidently pass the Associate Data Scientist in Python certification and thrive as a data scientist.
Associate Data Analyst
Database design is critical for a high-performance application. Just like you wouldn't build a house without a blueprint, you need to plan how you’ll store your data beforehand. In this interactive SQL track, you'll learn the fundamentals of database design and how to: ✓ Write basic SQL queries ✓ Group and aggregate data to produce summary statistics ✓ Join tables and apply filters and sub-queries ✓ Write functions to explore and manipulate data Working with real-world datasets, gain the SQL skills you need to query a database, analyze results, and effectively communicate your insights to stakeholders. There’s no prior SQL knowledge required—start your journey to confidently pass the Associate Data Analyst in SQL certification and thrive as a data analyst.
Data Analyst
Start your journey to becoming a data analyst using Python - one of the most popular programming languages in the world. No prior coding experience is required; you’ll start from scratch and learn how to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. You’ll begin your data analyst training with interactive exercises and get hands-on with some of the most popular Python libraries, including pandas, NumPy, Seaborn, and many more. You’ll learn why Python for data analysis is so popular and work with real-world datasets to grow your data manipulation and exploratory data analysis skills. As you progress through the courses, you’ll cover topics such as data manipulation and joining data. You’ll also learn key statistics skills, like hypothesis testing. Get started today, grow your Python skills, and begin your journey to becoming a confident data analyst.
Data Engineer
Advance your journey to becoming a Data Engineer with our Python-focused track, which is ideal for those with foundational SQL knowledge from our Associate Data Engineer track. This track dives deeper into the world of data engineering, emphasizing Python's role in automating and optimizing data processes. Starting with an understanding of cloud computing, you'll progress through Python programming from basics to advanced topics, including data manipulation, cleaning, and analysis. Engage in hands-on projects to apply what you've learned in real-world scenarios. You'll explore efficient coding practices, software engineering principles, and version control with Git, preparing you for professional data engineering challenges. Introduction to data pipelines and Airflow will equip you with the skills to design, schedule, and monitor complex data workflows.
Data Analyst
Learn how to master Power BI—one of the world’s most popular business intelligence tools—in this interactive learning path, co-created with Microsoft to pass the official PL-300 Data Analyst with Power BI exam. There’s no prior experience required! You’ll learn how to import, clean, manipulate, and visualize data in Power BI—all critical skills for any aspiring data professional. Through hands-on exercises, you'll learn data analysis best practices and discover a world of Power BI functionalities, including data modeling, DAX, Power Query, and many others. You'll also receive a 50% discount code for the Microsoft PL-300 certification after completing the track to help you supercharge your data analyst career!
Python Developer
Gain the career-building skills you need to successfully develop software, wrangle data, perform advanced data analysis, and become a Python developer. No prior coding experience is required; you can start your journey to becoming a Python developer today! In this track, you’ll learn how to manipulate data, write efficient Python code, and work with challenging data, including date and time data, text data, and web data using APIs. As your skills grow, you'll progress to writing Python functions and unit testing—an essential skill needed to find bugs in your code before your users do! Through interactive exercises, you'll also gain experience working with powerful Python libraries, including NumPy, pytest, and pycodestyle, that will help you perform key programming tasks such as web development, data analysis, and task automation. By the time you finish this track, you’ll have a firm grasp of what’s needed to become a Python developer and have the skills to get started as one.
Associate Data Scientist
Learn how to use R for data science, from data manipulation to machine learning, and gain the career-building R skills you need to succeed as a data scientist. As you progress through the courses in this track, you’ll explore how learning data science with R can help you to import, clean, manipulate, and visualize data. R is a versatile language for any aspiring data professional or researcher, and by learning the integral skills, you’ll develop a solid foundation for your data science journey. Through interactive exercises, you’ll get hands-on with some of the most popular R packages, including tidyverse packages like ggplot2, dplyr, and readr. You’ll work with real-world datasets as you write your own functions and learn foundational statistical and machine learning techniques. Start this track, grow your R programming and data science skills, and begin your journey to confidently pass the Associate Data Scientist in R certification and thrive as a data scientist.
Data Scientist
Master the skills you need to pass the Data Scientist in Python certification and prepare yourself for success in the field of data science. Throughout this track, you will focus on using Python for data science, starting with the basics and progressing to more advanced topics such as machine learning. You’ll cover a broad range of areas, including data manipulation, visualization, and analysis, using popular Python libraries such as pandas, Seaborn, Matplotlib, and scikit-learn. As you progress, you’ll work through interactive exercises using real-world datasets to help you test your abilities and develop your skills. These examples will help you explore various statistical and machine learning techniques, including hypothesis testing and predictive modeling. You’ll also gain an understanding of package development, data preprocessing, SQL for relational databases, Git for data science projects, and more. Complete this track to gain the knowledge and experience necessary to confidently pass the Data Scientist in Python certification and thrive as a data scientist.
Machine Learning Scientist
Master the essential Python skills to land a job as a machine learning scientist! With this track, you'll gain a comprehensive introduction to machine learning in Python. You’ll augment your existing Python programming skill set with the tools needed to perform supervised, unsupervised, and deep learning. You'll learn how to process data for features, train your models, assess performance, and tune parameters for better performance. This track also covers topics including tree-based machine learning models, cluster analysis, preprocessing for machine learning, and more. By the time you finish, you’ll have the confidence to use Python for machine learning, working with real data sets, linear classifiers, gradient boosting, and more. In the process, you'll get an introduction to natural language processing, image processing, and popular Python machine learning packages such as scikit-learn, Spark, and Keras.
Associate Data Engineer
In this track, you'll learn the fundamental concepts of data engineering, including the Extract-Transform-Load (ETL) and Extract-Load-Transform (ELT) workflows. You'll discover how to interact with relational databases such as PostgreSQL to store, modify, and query data. Moving through the track, you'll pick up techniques for querying structured data using SQL, including joining multiple tables, calculating aggregated statistics, filtering, grouping, and writing subqueries. Switching gears, you'll go on to discover database design principles such as star and snowflake schemas, and normalization. You'll use this knowledge to perform typical data engineering tasks such as creating, altering, and deleting tables, and enforcing data consistency by casting data to different data types. The track also shows how you can download PostgreSQL to your operating system, along with setting up and modifying users. Conclude by learning about data warehouse technologies and familiarizing with Snowflake, a popular cloud technology for data engineering!
Data Analyst
Gain the career-building R skills you need to succeed as a data analyst! No prior coding experience required. In this track, you’ll learn how to import, clean, manipulate, and visualize data in R—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular R packages, including ggplot2 and tidyverse packages like dplyr and readr. You’ll also develop your data manipulation and exploratory data analysis skills by working with a wide range of real-world datasets, including everything from U.S. income data to global food consumption. You’ll then gain the statistical skills you'll need to perform hypothesis testing. Start this track, grow your R skills, and begin your journey to becoming a confident data analyst.
Data Analyst
Learn how to master Tableau for data analysis, developing your skills and knowledge in one of the world’s most popular business intelligence tools. Throughout nine courses, you’ll learn how to use Tableau’s features to clean, analyze, and visualize data. This Tableau Data Analyst track requires no prior experience. Starting with the Tableau basics, you’ll explore how to analyze data and create dashboards before putting your newfound Tableau skills to the test with hands-on exercises and case studies. You’ll learn how to connect data, create impactful, presentation-ready data visualizations, and familiarize yourself with the feature of Tableau and how you can use them to your advantage. You’ll finish the track by learning how to leverage advanced calculations and apply statistical techniques. Once completed, you'll have most of the skills and knowledge required to pass Tableau’s Data Analyst certification, and you’ll have the confidence to use Tableau for your own data analyses.
Machine Learning Engineer
Step into the cutting-edge field of machine learning engineering with this comprehensive track designed for aspiring professionals. This program teaches you everything you need to know about model deployment, operations, monitoring, and maintenance. In this track, you will learn the fundamentals of MLOps. You will work interactively with key technologies like Python, Docker, and MLflow. You will learn in detail about concepts such as CI/CD, deployment strategies, or concept drift. The track includes interactive courses and real-world projects that help you facilitate the skills learned. Upon completing this track, you'll emerge as a well-rounded machine learning engineer with all the skills required for a junior machine learning engineer role. Note: Prior knowledge of concepts, including data manipulation, training, and evaluating machine learning models using Python, is expected from learners who enroll in this track.
SQL Server Developer
Learn the basics of database design and the different SQL data types. Then master the core concepts for the exam. In this track, you’ll learn how to write queries, functions, and stored procedures. You’ll also find out how to manage transactions, handle errors, and improve query performance.
Data Scientist
Master the skills you need to pass the Data Scientist in R certification and prepare yourself for success in the field of data science. As you progress through the courses in this track, you will focus on using R for data science. You will explore how learning data science with R can help you to import, clean, manipulate, and visualize data, and develop a solid foundation for your data science journey. You’ll cover a range of different skills, including data manipulation, visualization, and analysis, using popular R packages like ggplot2, dplyr, and readr. You will work with real-world datasets as you write your own functions and learn foundational statistical and machine learning techniques. You will also gain an understanding of SQL for relational databases and Git for data science projects, two essential tools for any data scientist. Through interactive exercises, you will get hands-on experience with R programming and the popular packages used in the field of data science. Completing this track will give you the knowledge and experience necessary to confidently pass the Data Scientist in R certification and thrive as a data scientist.
R Developer
Gain the career-building R programming skills you need to successfully develop software, wrangle data, and perform advanced data analysis in R. No prior coding experience is required, you can start your journey to becoming an R developer today! In this track, you'll learn how to manipulate data, write efficient R code, and work with challenging data, including date and time data, text data, and web data using APIs. As you become more comfortable with these skills, you'll move on to learn about writing functions in R and object-oriented programming—an essential skill for R developers working with large and complex programs. Through interactive exercises, you'll also gain experience working with powerful R libraries, including devtools, testthat, and rvest, that will help you perform key programmer tasks, such as web development, data analysis, and task automation. By the time you finish this track, you’ll have a firm grasp of what’s needed to become an R developer and have the skills to get started as one.
Statistician
Master the essential skills to land a job as a statistician! Using statistics, you can help solve real-world problems in business, engineering, the sciences, and many other fields. In this track, you'll learn how to use statistical methods to explore and model data, draw conclusions from a wide variety of datasets, and interpret and report findings.
Quantitative Analyst
In finance, quantitative analysts ensure portfolios are risk balanced, help find new trading opportunities, and evaluate asset prices using mathematical models.
Machine Learning Scientist
Master the essential skills to land a job as a machine learning scientist! You'll augment your R programming skillset with the toolbox to perform supervised and unsupervised learning. You'll learn how to process data for modeling, train your models, visualize your models and assess their performance, and tune their parameters for better performance. In the process, you'll get an introduction to Bayesian statistics, natural language processing, and Spark.
Not what you're looking for? Skip this survey and go see our skill tracks, career tracks, and courses.