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Certificate (San Francisco)

Data Science

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PROFESSIONAL CERTIFICATION

Data Science Course San Francisco

  • Live Classroom
  • Part-Time
  • Expert Instructors

BrainStation’s Data Science course was created to help you develop job-ready data skills. Earn a Data Science certificate while learning the foundations of data science, how to create dynamic data visualizations, data modeling, machine learning techniques, Python for data analysis, and more.

View the Course Package to access:

  • Tuition details and scholarships
  • Financing options
  • Employer sponsorship

Next Kickoff:

January 17

6:30 pm - 9:30 pm EST

Enroll Now

Limited Capacity

Find a class that fits your schedule.

4.5 out of 5 stars Google
4.7 out of 5 stars Course Report
4.8 out of 5 stars Switchup

Learn Data Science in San Francisco

With the rise of big data, top companies around the world need teams of Data Scientists to collect, organize, model, and examine large amounts of data. In BrainStation’s data science courses, you will learn the foundations of data science and perform an end-to-end statistical analysis, learn to make data-driven predictions, and present results in a data visualization.

Learn Data Science in San Francisco

Online classroom. Live and expert-led.

Build Data Science Skills

Ideal for learners looking to upskill.

Get Ready For Data Science Jobs

Build an interview-ready data science portfolio project.

Data Science Certification

Earn a BrainStation Data Science Certificate.

Data Science Courses

Ready to start learning data science? Take BrainStation’s data science courses online or in-person at any of BrainStation’s campuses. See below for our list of upcoming data science courses.

First Class Last Class # of Classes Class Times
January 17 March 21 March 21 10 Tuesdays 3:30pm - 6:30pm PST Enroll Now
January 19 March 22 March 22 10 Thursdays 6:30pm - 9:30pm PST Enroll Now
January 19 March 23 March 23 10 Thursdays 10:30am - 1:30pm PST Enroll Now
February 7 April 10 April 10 10 Tuesdays 6:30pm - 9:30pm PST Enroll Now
February 7 April 11 April 11 10 Tuesdays 10:30am - 1:30pm PST Enroll Now
February 9 April 13 April 13 10 Thursdays 3:30pm - 6:30pm PST Enroll Now
March 14 May 16 May 16 10 Tuesdays 3:30pm - 6:30pm PDT Enroll Now
March 15 May 16 May 16 10 Wednesdays 6:30pm - 9:30pm PDT Enroll Now
March 16 May 18 May 18 10 Thursdays 10:30am - 1:30pm PDT Enroll Now
Campus classroom preparing for class

This Course is Offered Online in San Francisco

Campus classroom preparing for class

This Course is Offered Online in New York

Campus classroom preparing for class

This Course is Offered Online in Miami

First Class Last Class # of Classes Class Times
January 18 March 22 March 22 10 Wednesdays 6:30pm - 9:30pm GMT Enroll Now
February 20 May 15 May 15 10 Mondays 6:30pm - 9:30pm GMT Enroll Now
March 30 June 8 June 8 10 Thursdays 6:30pm - 9:30pm BST Enroll Now
First Class Last Class # of Classes Class Times
January 17 March 21 March 21 10 Tuesdays 6:30pm - 9:30pm EST Enroll Now
February 23 May 4 May 4 10 Thursdays 6:30pm - 9:30pm EST Enroll Now
March 29 May 31 May 31 10 Wednesdays 6:30pm - 9:30pm EDT Enroll Now
Campus classroom preparing for class

This Course is Offered Online in Vancouver

Unit 1

Introduction to Data Science

The Python programming language has emerged as an essential tool for Data Scientists. In the first unit of BrainStation’s Data Science certification course, you will learn Python for data science through a series of hands-on data science projects. You will learn data manipulation techniques, how to analyze data, and how to use NumPy, Pandas, and the best Python libraries for data science, helping you to build a strong foundation for what you’ll learn throughout the rest of the Data Science course.

  • Python
  • Anaconda
  • Notebooks
  • NumPy
  • Pandas
Key Skills:
Python Coding
Data Manipulation
Data Organization
Programming Fundamentals

Python for Data Science

Python is one of the most important tools for a Data Scientist. Through real-world projects, quickly get up to speed with the Python and programming basics you'll need in the field of data and as a future Data Scientist.

Python Libraries for Data Science

Learn how to apply Python packages like NumPy and Pandas to perform practical, real-world data analysis and uncover business analytics insights.

Data Analysis Techniques

Discover how a Data Scientist can integrate different data sets in order to discover new actionable insights by using techniques such as joins, sorting and grouping, and transforming and aggregating.

Unit 2

Data Wrangling and Data Cleaning

A Data Scientist requires great data to perform great data analysis. Learn data cleaning and data wrangling techniques to ensure your data is organized, structured, and consistent. Learn to translate raw data into interesting data visualizations, and use Python packages to facilitate additional statistical analysis, so you can understand how to tell a story with data and get the most out of your work.

  • Python
  • Seaborn
  • Unit 2 tool: bokeh.svg
  • Unit 2 tool: matplotlib.svg
Key Skills:
Data Analysis
Data Wrangling
Data Visualization

Beautiful Data Visualization

Using Python packages, learn to create different types of data visualization. Understand the use cases for different data visualization examples so you know when to use them.

Prepare Data

Learn the essentials of data cleaning and data wrangling so you can prepare your data sets for statistical analysis, modeling, and decision making.

Unit 3

Data Modeling

Review important statistical analysis concepts and learn how they apply to data modeling and decision making. Using real data problems encountered in the data science field, learn to build both linear and categorical models, and understand when to use them. Practice applying these techniques to create data models that help you make a predictive analysis.

  • Python
  • Pandas
  • NumPy
  • Unit 3 tool: matplotlib-white.svg
  • Statsmodels
Key Skills:
Statistics
Data Relationships
Hypothesis Testing
Data Modeling
Python Data Visualization
Predictive Analytics & Extrapolation

Statistics for Data Science

Review statistics foundations like the measures of central tendency and dispersion, covariance, and correlation, and understand how to incorporate them into your data analysis.

Hypothesis Testing

Practice how Data Scientists perform hypothesis testing as part of their exploratory data analysis. Learn how to calculate and apply statistical significance, and more.

Data Models

Learn different modeling techniques for numerical and non-numerical data. Build and run various types of data science models on real datasets to uncover patterns and make predictions.

Unit 4

Introduction to Machine Learning

Machine learning has emerged as a truly disruptive technology and data science capability. Discover common machine learning techniques and machine learning algorithms, and learn how they’re applied in practical, real-world scenarios.

  • Python
  • Pandas
  • NumPy
  • Scikit-learn
  • SciPy
Key Skills:
Machine Learning Fundamentals
Data Classification Models
Decision Trees
Model Evaluation
Categorical Predictions

Machine Learning Basics

Discover what machine learning is and how to apply it effectively within the real world. By understanding the constraints and applications of machine learning, you’ll be prepared to identify opportunities to implement it.

Machine Learning Models

Learn a variety of machine learning methods and machine learning algorithms, along with the scenarios they are used in. Explore models like decision trees, Naive Bayes classification, regression model evaluation, cross-validation, and more.

Data Scientist Course Instructors

Instructors in BrainStation’s data science courses are experienced data professionals who work at the world's most innovative companies. In our data science classes, you’ll learn from experts who have years of data industry experience and who know the most up-to-date and practical data skills companies around the world are looking for.

Yann Kiraly

Yann Kiraly

Product Analyst, Data Science at Google

Nada Salem

Nada Salem

Data Scientist & Product Manager at Spotify

Olga Milkovska

Olga Milkovska

Senior Insights Analyst at LinkedIn

Isaac White

Isaac White

Principal Measurement Lead at Google

Wenjie Sun

Wenjie Sun

Product Analyst at Google

Yann Kiraly

Yann Kiraly

Product Analyst, Data Science at Google

Nada Salem

Nada Salem

Data Scientist & Product Manager at Spotify

Olga Milkovska

Olga Milkovska

Senior Insights Analyst at LinkedIn

Isaac White

Isaac White

Principal Measurement Lead at Google

Wenjie Sun

Wenjie Sun

Product Analyst at Google

Industry-Led Data Science Training

BrainStation partners with industry experts when building all of our courses, ensuring every course covers the latest industry-relevant topics and tools businesses need. We continue to work with our network of experts to update our courses so they're always up to date.

Build Your Data Science Portfolio

Showcase everything you’ve learned with a unique Data Scientist portfolio project by completing a real-world analysis on a data set of your choosing. Every week you’ll be provided with clear steps to develop your final data science project. By the end of the Data Science course, you’ll have used programming to collect data and complete data wrangling, developed a hypothesis, and modeled your data to prove or disprove it. Finally, you’ll construct a data visualization to present your insights in a meaningful way.

project screenshots

View Tuition, Financing Options, and More in the Course Package

View the Course Package to access:

  • Tuition details and scholarships
  • Financing options
  • Employer sponsorship

Earn a BrainStation Data Science Certificate

Upon completing BrainStation’s Data Science Course, you’ll receive an industry-recognized professional certificate to share with your network and showcase all that you’ve learned. BrainStation certificates are formatted for sharing on LinkedIn.

What Our Graduates Are Saying

Dylan Hebb

Dylan Hebb

Senior Consultant at Content Bloom

When you take a BrainStation course, you're learning with some of the very best in the industry. You collaborate with product managers, digital strategists, UX designers, and all kinds of other backgrounds.

#brainstation #BeFutureProof #LearningAtBrainStation #remotelearning

Andrew Gosine

Andrew Gosine

Product Designer

Our instructor... was clear, detail oriented, and made the learning environment safe and collaborative. We got a lot of real world examples from him, and all the little details he shared made this entire course special, and more than simply reading a textbook.

Overall, I'm a big advocate for Brainstation's courses - they've proved to be extremely valuable in my career.

Chandni Shah

Chandni Shah

People Analytics Partner at AIG

The knowledge I gained through BrainStation supports my career by enabling me to do my role more confidently and efficiently... The most valuable skill I learned was being comfortable with being uncomfortable. Expanding your horizons can cause short-term discomfort in exchange for long-term growth.

Read Full Testimonial
Aiden Feltkamp

Aiden Feltkamp

The data science course is great... Through this class, I learned how to clean and model data, which is the basics of machine learning. The teachers were fantastic and they related everything to practical use. It's fast-paced, but the teachers are great at keeping you up to speed. I would highly recommend this class to anyone who's looking to start on machine learning and data modeling.

Join our growing community of 15,000+ alumni.

Data Science Certification FAQs

Data Science 101

What Is the Difference Between Data Science and Data Analytics?

If you want to become a Data Scientist, you should know this is not the same thing as becoming a Data Analyst, which is typically a more junior position. A Data Scientist, generally speaking, has more technical knowledge and expertise, and data science positions are usually more senior in nature compared to data analysis positions.

BrainStation’s Data Science course can be considered an intermediate-level data science course, as it dives into prescriptive and predictive analytics, machine learning, artificial intelligence, statistical analysis, and programming languages. BrainStation’s Data Analytics course, on the other hand, is more beginner-friendly with a focus on descriptive analytics, business intelligence, and the industry-standard tools and software Data Analysts need to learn to use like Microsoft Excel and SQL databases.

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