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.
Learn live online from experienced industry leaders, for 3 hours a week for 8 weeks.
Learn live from experienced industry leaders
Rajwinder Singh Walia is an experienced professional who brings years of experience into the classroom to teach you essential skills.
Find a class that fits your schedule.
The Instructors are very knowledgeable, but they’re also passionate about what they’re doing and that's the best way to share their knowledge and experience.
Mohamed Touré
Data Scientist at Shopify
Learn Data Science in New York
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 New York
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.
Learn in-person from experienced industry leaders, for 3 hours a week for 8 weeks.
Learn live from experienced industry leaders
BrainStation instructors are experienced professionals who brings years of experience into the classroom to teach you essential skills.
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
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
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.
Nada Salem
Data Scientist & Product Manager at Spotify
Wenjie Sun
Product Analyst at Google
Isaac White
Principal Measurement Lead at Google
Olga Milkovska
Senior Insights Analyst at LinkedIn
Yann Kiraly
Product Analyst, Data Science at Google
Nada Salem
Data Scientist & Product Manager at Spotify
Wenjie Sun
Product Analyst at Google
Isaac White
Principal Measurement Lead at Google
Olga Milkovska
Senior Insights Analyst at LinkedIn
Yann Kiraly
Product Analyst, Data Science 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.
View Tuition, Financing Options, and More in the Course Package
View the Course Package to access:
Tuition details
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.
Location
Learn in the Center of NYC
Located in the heart of the tech & retail district of SoHo Manhattan, BrainStation is at the center of New York’s cultural and tech scene, surrounded by the best tech companies in NYC. In addition to courses, BrainStation New York offers training sessions, industry events, expert panel discussions, and more.
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.
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.
Mohamed Touré
Data Scientist at Shopify
Everyone who wants to achieve a career goal, learn a new skill, or gain more knowledge in a certain field should not be afraid to take the next step. Taking a course at BrainStation is a great opportunity – the skills you’ll learn are very practical and the learning experience and environment are made for professionals who really want to learn.
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 30,000+ alumni.
Data Science Certification FAQs
Will I earn a Data Science certificate from this course?
Yes, when you complete the Data Science course, you will earn a BrainStation Data Science certificate, which can boost your LinkedIn profile and resume. Data science certifications, whether from in-person or online data science courses, can help you stand out in the job market and when applying for data science jobs and positions.
What payment options do you offer?
BrainStation offers some of the most competitive payment options for data science training, with a range of flexible payment plans.
These include:
Monthly payment installments
Allowing you to split your tuition into smaller monthly payments.
Employer sponsorship
Get your tuition reimbursed by your employer.
Are there any prerequisites for this Data Science course?
BrainStation’s Data Science course is an intermediate-level course. Experience programming with Python is needed and some prior knowledge of statistics is recommended. If you are new to Python, BrainStation’s Python course is at a beginner-level, and can help you prepare for data science and machine learning training.
What Data Science tools and programming languages will we learn in BrainStation’s Data Science course?
By taking BrainStation’s Data Science certification programs, you will gain first-hand experience with Anaconda and Jupyter Notebooks, and you will learn to program with Python, one of the most high-demand programming languages used by Data Scientists.
You will use data science and Python to import, clean, manipulate, and analyze various types of data. You will then learn to build linear models for numerical data and categorical models for non-numerical types of data. Finally, using Python packages, you will construct data visualizations that can help tell a story with the analyses and predictions of a professional, polished Data Scientist.
What is the difference between BrainStation’s Data Science course and the Data Science bootcamp?
BrainStation's Data Science course is a flexible, professional development course offered on a part-time basis. Taught by industry experts, the Data Science course is a project-based, hands-on learning experience, allowing you to develop high-demand data science skills and learn the latest data tools and technologies.
BrainStation's Data Science bootcamp, on the other hand, is an intensive learning experience designed to transform your skillset and help you launch a new career in data. Throughout the program, students develop and complete five projects including one major portfolio piece, using real-world data, data mining, big data, natural language processing, and practical machine learning skills. By the end of the program, graduates will have the skills, experience, and portfolio needed to dive into a career in data as Data Scientists.
How long are BrainStation's Data Science courses?
BrainStation Data Science courses are typically 4 to 8 weeks long depending on the delivery format, as students can choose whether to take courses on weekends or evenings.
In that time, you will master core data science methodology, learn how to understand a variety of machine learning models, and develop key data visualization skills. BrainStation Data Science courses are immersive and hands-on, allowing you to complete data science projects and graduate with a polished professional portfolio.
Can I take this course online?
Yes, you can take BrainStation Data Science courses online.
BrainStation's online Data Science certificate course is taught by leading industry experts in a live, interactive classroom environment. Our project-based online course encourages collaboration and communication between classmates, who work together on cross-disciplinary teams to create real-life projects that eventually become the basis of their professional portfolios.
Students in our online Data Science courses stay in touch with each other and instructors alike through BrainStation's industry-leading student learning platform, as well as a lively Slack community, which provides support and updates even beyond graduation.
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.
What Can I Learn in a Data Science Course?
In a data science course, you can learn the fundamentals of working with and analyzing data, how to leverage data and statistical analysis skills to make actionable data-driven predictions, and how to present your findings in compelling data visualizations.
The best data science certifications will begin by imparting the most crucial and foundational aspects of data analysis and data management, including data wrangling, data cleaning, data processing, and data manipulation techniques, while also developing your programming skills with Python and R, two essential programming languages for data science. From there, students should master the art of storytelling with data visualizations, as they learn how to decide which data visualization approach to most effectively represent their data, and how to use Python packages to facilitate further statistical analysis.
Top data science certifications will also delve into more complex data science concepts relating to machine learning workloads, algorithms and techniques, data classification models, predictive modeling, decision trees, data processing systems, and more.
What Are the Most In-Demand Data Science Jobs?
Some of the most in-demand data science jobs include Data Scientist, Data Analyst, Data Engineer, Machine Learning Engineer, Data Architect, Database Administrator, and more.
Because the demand for data skills is high and rising, almost all professional job roles along the Data Scientist career path can be considered in high demand. The U.S. Bureau of Labor Statistics forecasts that the demand for Data Scientists — defined as computer and information research scientists — will grow 22 percent by 2030, significantly faster than the rate of growth for other job roles.
Data skills and concepts are also increasingly crucial to a variety of other jobs and disciplines, including business analysis, cybersecurity, product management, and more.
How Can I Get into Data Science?
To get into data science, you should learn data fundamentals and key programming languages for data science, consider gaining formal training through data science courses, work on data science projects and data visualizations, and finally look for freelance work, internships, or entry-level data science jobs.
Learning the basics of data could be easier if you have a background in related fields including web development (specifically, if you have experience with R or Python programming), computer science, statistical analysis, or data analysis.
Even if you do have experience in a related field, however, a Data Scientist requires experience with many specialized tools, techniques, strategies, and concepts that are relatively unique to the field. That's why most consider certification programs to be an important step along a data science career path, ensuring that you have the specific skills needed to thrive as a Data Scientist.
What Is the Best Way to Stay on Top of Data Science Trends?
The best way to stay on top of data science trends is to read data science and data engineering blogs and email newsletters, attend networking events and conferences, join online communities of Data Scientists, and read recent research papers by top data science professionals.
Large tech companies including Meta, Netflix, Uber, Airbnb, and Google regularly publish blog articles on the latest innovations in data science, artificial intelligence, machine learning, and natural language processing. For a more Senior Data Scientist who is open to some rigorous academic reading, notable new research on data science and other related topics is being published all the time, and there are plenty of online sources curating that research to help you find the most impactful work.
Networking with colleagues, whether in-person or in robust online communities such as Kaggle and Reddit, is another essential part of keeping up with data science trends. BrainStation regularly holds panel discussions with top industry experts, thought leadership events, and other networking gatherings to give students opportunities to build their professional networks while also discussing the most current trends and issues in their fields.
What Skills Should I Learn for a Data Science Career?
Key skills you should learn for a data science career include data wrangling, data cleaning, querying data, data engineering, data management, using the Python programming language for a variety of applications, data analysis, data visualization, predictive modeling, machine learning techniques, and more.
Clearly, Data Scientists need strong data skills, which means not only having the technical skills necessary to organize, manipulate, extract, transform, and analyze data, but also the business sense to understand how to pull actionable insights from that data that could help companies make better data-driven decisions.
In other words, many Data Scientist job responsibilities require a combination of soft and technical skills. Creating compelling data visualizations, for instance, means not only understanding how to use data science tools like Tableau, PowerBI, and Python, but also having the communication skills to understand how to present that information in a persuasive and accessible way.
How to Prepare for a Data Scientist Course
To prepare for a Data Scientist course, you should look into free online resources on key data science methodologies and techniques, gain clarity on your educational goals, and explore the events and resources that could be provided by the school you are planning to attend.
Before you start a data science certification course, you could explore a free online Python tutorial to build out your basic coding skills, browse the web for great data visualization examples to inspire you, and even consider searching for free datasets and open-source tools online to work on data science projects at your own pace.
Ultimately, BrainStation's Data Science professional certificate course was designed to help learners without extensive experience master the foundations of data science, but this kind of preparatory work can only help put you in a position to succeed once you begin the course.
Why Is This the Best Data Science Course for Me?
BrainStation's Data Science course is the best data program because our hands-on, project-based learning experience gives students real-world data experience. The course's innovative curriculum covers the most current-possible strategies and tools, and our live online courses are led by experienced data science professionals with a thorough understanding of what it takes to succeed as a Data Scientist.
BrainStation's Data Science certification course is ideal for learners looking to boost their skills, either to establish a new career in data science or to gain valuable data analytics skills that would be valuable to any number of fields, including product management, business analytics, cybersecurity, and web development. As you learn data science online, you will collaborate with other students and ultimately get the opportunity to complete real-world data projects that will form the basis of your professional portfolio in data science.
To then help students leverage their new data science expertise to meet their professional goals, BrainStation offers networking opportunities, thought leadership events, and panel discussions featuring experts from our global hiring partner network of top companies.
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