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Data Science Data Science

Data Science

Create robust predictive models with statistics and Python programming. Build confidence and credibility to tackle complex machine learning problems on the job.

Learn more about this course



Analysts have the opportunity to derive insights and build predictive models for business needs ranging from customer segmentation to personalised product recommendations.

In this training, participants build on Level 1 Data Skills to practice advanced analytics and explore machine learning in Python.


This is a fast-paced course with some prerequisites.

Students should be comfortable with programming fundamentals, core Python syntax, and basic statistics.

Upon enrolling, you’ll complete a short onboarding task and, based on your results, may be advised to take an introductory Python workshop.


Analysts or engineers who want to break into data science.

Managers who need to work with technical teams and want to more effectively communicate and empathise with them.


Level 1 Data Skills: Wrangle, explore, model, and communicate the results of multiple analyses with Python and its many packages

Level 2 Data Skills: Work on advanced analytics data sets and explore the capabilities of machine learning

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Course Outline

Unit 1: Programming Basics
  • Practice Python programming basics, work in a development environment using git and GitHub.


Unit 2: Research Design and Exploratory Data Analysis
  • Practice exploratory data analysis for cleaning and aggregating data and understanding the basic statistical testing values of your data.


Unit 3: Foundations of Data Modeling
  • Create linear and logistic regression models, and branch from statistics into machine learning with kNN and classification.


Unit 4: Machine Learning
  • Learn and practice core machine learning models (decision trees, random forests, NLP, time series) to evaluate complex problems.

Inside Our Best-in-Class Curriculum

Real-World Portfolio Projects

Graduate with a polished capstone project that uses machine learning to solve a data problem. Develop a predictive model, technical documentation, and stakeholder presentation.

Individualised Instructor Support

Get guidance, feedback, and more from experts who are dedicated to supporting your learning and career goals. Get individual feedback and guidance from instructors and TAs during office hours. Stay motivated and make the most of your experience with the help of GA's dedicated team. 

Global Network of 100K+ Alumni

Create connections with peers that last well beyond your time in the classroom. As part of the GA alumni community, you’ll gain access to networking events and workshops to keep evolving your career for years to come.

Elite Instructors

These data science professionals and entrepreneurs bring in-depth experience from the field to the classroom each day, providing invaluable insights into succeeding on the job. 

GA instructors* are committed to providing personalised feedback and support to help you gain confidence with key concepts and tools.

*GA instructors are subject to their availability

Frequently Asked Questions

Why is a data science skill set relevant today?

Companies of all stripes use data science to take on today’s biggest challenges, tackling everything from public policy and robotics to dating and eCommerce. As a result, organisations are moving quickly to build robust in-house teams of data scientists and advanced analysts, and there’s not enough talent to go around.

According to Burning Glass, “Data science and analytics skills are now widely in demand in decision-making roles, including managers across a range of industries. In fact, our data shows that more than 1.7 million job postings asked for data science skills in 2018.” Learning this future-proof skill set can help you enter the next stage of your career, whether that’s advancing in your current profession or exploring an exciting and lucrative field.

What are the backgrounds of data science students?

This course is designed for data professionals who want to perform complex analysis to power predictions and add marketable skills to their resume. You’ll find a diverse range of students in the classroom: 

Data analysts, marketing analysts, BI analysts, or consultants who work with big data and need to upgrade their skills. Software engineers who want to apply their programming skills toward a new career. Other professionals with a quantitative background eyeing a transition to tech.

Ultimately, this programme attracts a community of eager learners who have an interest in manipulating large data sets and forecasting to impact strategy and bottom lines.

Who teaches this course?

Our instructors represent the best and brightest data professionals from top companies like Atlassian, Capital One, and Deloitte. They combine in-depth experience as practitioners with a passion for nurturing the next generation of talent.

We work with a large pool of experienced instructors around the world.

What does my tuition cover?

Here are just some of the benefits you can expect as a GA student:

  • 60 hours of expert instruction designed to build a well-rounded foundational data science skill set.

  • Up to 25 hours of self-paced pre-work to brush up on programming fundamentals and statistics.

  • Robust data science coursework, including expert-vetted lesson decks, lab materials, and more. Refresh and refine your knowledge throughout your professional journey as needed.

  • A portfolio-ready capstone project built with support from your instructor.

  • Individual feedback and guidance from instructors and TAs during office hours. Stay motivated and make the most of your experience with the help of GA’s dedicated team.

  • A data science certificate to showcase your new skill set on LinkedIn.

  • Connections with a professional network of instructors and peers that lasts well beyond the course. The global GA community can help you navigate and succeed in the data science field.

Are there any prerequisites?

This is a fast-paced course with some prerequisites. Students should be comfortable with programming fundamentals, core Python syntax, and basic statistics.

Upon enrolling, you’ll complete a short onboarding task and, based on your results, may be advised to take an introductory Python workshop. You’ll also complete up to 25 hours of online preparatory lessons that will ensure you have the foundations to dive into rigorous coursework.

Our Admissions team can discuss your background and learning goals to advise if this course is a good fit for you.

Will I earn a certificate?

Yes! Upon passing this course, you will receive a signed certificate. Thousands of GA alumni use their data science certificate to demonstrate skills to employers and their LinkedIn networks. GA’s Data Science course is well-regarded by many top employers, who contribute to our curriculum and use our data courses to train their own teams.

Can I work full-time while enrolled in this course?

Yes! All of our part-time courses are designed for busy professionals with full-time work commitments. 

You will be expected to spend time working on homework and projects outside of class hours each week, but the workload is designed to be manageable with a full-time job.

If you need to miss a session or two, we offer resources to help you catch up. We recommend you discuss any planned absences with your instructor.

What projects will I work on during the course?

For your capstone project, you’ll apply machine learning techniques to solve a real-world problem. You’ll develop a model, technical documentation, and stakeholder presentation, and graduate with a polished, portfolio-ready data science project to showcase your skills. We encourage you to tackle a problem that’s related to your work or a passion project you’ve been meaning to carve out time for.

Throughout the course, you’ll also complete a number of smaller projects designed to reinforce what you’ve learned in each unit.

How does this course relate to GA’s other data programmes?

This Data Science course assumes some prerequisite knowledge and is designed for professionals who already work with data and want to perform more complex analysis involving computation.

If you’re searching for a more entry-level course, Data Analytics teaches beginners how to perform rigorous analysis with Excel, SQL, and Tableau.

For those committed to a career change, the full-time Data Science Immersive programme provides the most direct pathway to data science and other advanced analytics roles.

Which format should I take this course in — on campus or online?

It’s up to you! Our Remote courses offer a learning experience that mirrors GA’s on-campus offerings but allow you to learn from the comfort of home. If you have a busy travel schedule, or just want to save yourself the commute, a Remote course could be a good option for you. You’ll still get access to the expert instruction, learning resources, and support network that GA is known for.

If you prefer to learn alongside your peers and can make it to campus twice a week, our in-person courses allow you to take advantage of our beautiful classrooms and workspaces.


Our Admissions team can advise you on the best format for your personal circumstances and learning style.