Accelerate your career with the globally recognized BrainStation Data Science Certification (DSC™), through hands-on experience in live courses taught by data science leaders from global tech companies.
Learn live online from experienced industry leaders, for 3 hours a week for 8 weeks.
Learn live from experienced industry leaders
Tanvi Kalevar is an experienced professional who brings years of experience into the classroom to teach you essential skills.
Find a class that fits your schedule.
Get Certified in Data Science
Gain essential Data Science skills with hands-on instruction from industry leaders working at the best global tech companies like Amazon, Meta, and Microsoft.
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
Data Scientist at Shopify
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
Data Scientist at Shopify
Data Science Certification (DSC™) Course Overview
DSC-2024Q3
Concepts
Data Science Workflow
Virtual Environments
Numerical Analysis
Vectorization and Arrays
Data Cleaning
Data Visualization
Storytelling
Data Insights
Statistical Analysis
Statistical Modeling
Machine Learning
Neural Networks
NLP
Text Analysis
Natural Language Understanding (NLU)
Natural Language Processing (NLP)
Natural Language Generation (NLG)
Text Representation
Large Language Models (LLMs)
Transformers
Attention Mechanism in LLMs
Data Science Workflow
Data Insights
Natural Language Understanding (NLU)
Virtual Environments
Statistical Analysis
Natural Language Processing (NLP)
Numerical Analysis
Statistical Modeling
Natural Language Generation (NLG)
Vectorization and Arrays
Machine Learning
Text Representation
Data Cleaning
Neural Networks
Large Language Models (LLMs)
Data Visualization
NLP
Transformers
Storytelling
Text Analysis
Attention Mechanism in LLMs
Frameworks
Problem Space Analysis
Data Science Lifecycle
Data Mining Process
Problem Space Analysis
Data Science Lifecycle
Data Mining Process
Skills
Python Programming
Key Performance Indicator (KPI) Design
Exploratory Data Analysis (EDA)
Data Wrangling
Data Cleaning
Data Visualizations in Python
Statistical Analysis
Descriptive Statistics
Hypothesis Testing
A/B Testing
Data Modeling
Predictive Analysis
Machine Learning
Linear Regression
Classification Modeling
Model Evaluation
Model Optimization
Deep Learning
NLP
Industry tools
Python
Anaconda
Jupyter Notebook
NumPy
Pandas
Seaborn
Matplotlib
Plotly
Bokeh
SciPy
Scikit-Learn
Natural Language Toolkit (NLTK)
Why Get Certified in Data Science
Taught By Leaders From Top Global Tech Companies
Receive hands-on training from data science leaders working at companies like Amazon, Meta, and Microsoft.
Build Your Data Science Portfolio
Build a data science portfolio that demonstrates your unique expertise and experience.
Globally Recognized By Top Companies
BrainStation certifications are globally recognized by top companies for the most advanced and up-to-date skills.
Data Science Success Stories
I started by learning some things on my own, but eventually realized that a classroom setting would get me to where I wanted to be a lot faster.
Daria Aza
Machine Learning Engineer at Shopify
Data Science Course Start Dates
Take the Data Science Certification online or in-person at any of BrainStation's campuses.
Select a time that fits your schedule.
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 bring years of experience into the classroom to teach you essential skills.
This Course is Offered Online in
Vancouver
Data Science Certification Course Curriculum
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
Bokeh
Matplotlib
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
Matplotlib
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.
Earn Your Data Science Certification (DSC™)
Successfully completing BrainStation’s Data Science Certification course will earn you the globally recognized BrainStation Data Science Certification (DSC™), demonstrating your mastery of the latest cutting-edge skills and tools. Add this credential to your LinkedIn profile and resume or CV.
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Your Next Step Towards Data Science Certification
View the Data Science Course Package to Learn More.
View the Course Package to access:
Tuition details
Financing options
Employer sponsorship
Join BrainStation's Global Alumni Network
With a BrainStation certification, you’ll join our global alumni network: a community of accomplished professionals across a range of critical tech skills, including Data Scientists.
30,000+
Global BrainStation Alumni
100+
Countries
Industry-Led Data Science Certification
BrainStation’s globally recognized certifications are created by industry professionals, for industry professionals. Our network of experts from leading tech companies provide insights and guidance to ensure each certification demonstrates the latest cutting-edge skills and tools.
Location
Learn in Miami’s Vibrant Wynwood Community
Located in the heart of Wynwood, BrainStation is at the center of Miami’s tech scene, surrounded by the best tech companies in Miami. In addition to courses, BrainStation Miami offers bootcamps, courses, industry events, expert panel discussions, and more.
The Data Science Certification (DSC™) at BrainStation is a leading professional certification that verifies your completion of the course. Upon course completion, graduates receive the certificate and become a BrainStation-Certified Data Science Practitioner. A BrainStation certification can boost your LinkedIn profile and resume, helping you stand out in the job market when applying for Data roles. BrainStation has been a global leader in digital skills training since its inception in 2011 and has trained over 30,000 professionals around the world.
Is my professional background a good match for the course?
While in-depth, all of BrainStation’s certification courses are designed to be compatible with individuals from various professional backgrounds. The Data Science Certification course is considered beginner-friendly and is open to anyone looking to transition into data science, or enhance their existing skills.
What are the prerequisites for enrolling in a Data Science Certification course?
BrainStation's Data Science course was created for those who are new to data but are interested in a career as a Data Scientist. The course is designed for individuals looking to transition into a data role or enhance their existing skills. It is considered to be beginner-friendly and requires no prior experience for admission.
Who are the instructors?
BrainStation's Data Science instructors are seasoned leaders who actively work in roles at top companies like Amazon, Meta, and Google. They bring real-world experience from working on digital products used by millions, offering real-world examples and unique insights into what it takes to get hired and thrive in a data role.
What are the classes like?
BrainStation's Data Science Certification classes are immersive and hands-on right from day one. You’ll work on real-world projects, use industry-standard tools, participate in group exercises, and develop portfolio content that showcases your skills. Throughout the sessions, you’ll build a strong foundation in data concepts and frameworks, and by the end, you’ll have practical experience and the confidence to continue your journey to your first data role or promotion.
What Data Science tools and programming languages will we learn in BrainStation’s Data Science course?
You'll have exposure to essential tools like Python for data manipulation, Jupyter Notebooks for interactive coding, and libraries like NumPy and Pandas for data processing. The course also covers Seaborn for data visualization and Scikit-learn and SciPy for machine learning and scientific computing. Together, these tools equip you with practical skills for real-world data science applications.
How many students are in each class?
We prioritize creating an engaging and tailored learning experience by keeping our class sizes small enough to ensure that everyone receives focused support from the instructor, but large enough that learners have the opportunity to build valuable connections and benefit from the unique perspectives of professionals from diverse industries.
Is the course online or in-person?
Both! You can take BrainStation's Data Science Certification course in person at one of our campuses or in an online live format. Whether digital or in-person, you will be participating in a live, interactive classroom environment taught by a leading Data Science expert.
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 that provides support and updates even beyond graduation. There are several dates and times to offer flexibility for remote learning, and the course is designed to fit around professional schedules. Check out the course kick-off schedule here.
How long is the course, and what is the schedule?
BrainStation's Data Science course is typically 4 or 8 weeks long, depending on the delivery format — currently offered in either 8 evening classes or 4 weekend day classes. In either case, the course adds up to a total of 24 hours of training, case studies, projects, lectures, and more. Our course schedule is designed to give you ultimate flexibility with delivery format, days of the week, and length. Check out the course kick-off schedule here.
What kind of roles can I apply for after completing the certification?
After completing the Data Scientist Certification (DSC™), you can apply for roles such as Data Analyst, Data Scientist, or Business Intelligence Analyst. With experience, you can also pursue advanced roles like Senior Data Scientist, Data Lead, or even Director-level roles depending on your background and industry focus.
How does a Data Science Certification compare to a Degree or Master's program?
A certification provides targeted learning and immediate recognition of specific skills, making it ideal for data professionals looking to quickly validate their expertise and stand out in the job market. Unlike a degree or Master’s program, which takes longer and covers a wider range of topics, certifications are streamlined and practical, allowing you to apply new skills directly to your role. This makes certifications a great option for those looking to advance their careers efficiently without the time and financial investment of a traditional degree.
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. Learn More here: Data Science Bootcamp Online
What payment options do you offer?
BrainStation offers some of the most competitive payment options for Data Science training. Payment options include:
Scholarship discount programs
Partial scholarships are available to help with tuition and are subject to eligibility. about these options.
Monthly payment installments
Split your tuition into smaller amounts and pay in installments over 3, 6, or 12 months.
Employer sponsorship
Many learners can have their tuition reimbursed by their employer through established Learning & Development budgets or on an ad-hoc basis.
Can I speak to someone about the course before I start?
Definitely! Our team of learning advisors is here to answer any questions you have. Simply at a time that is convenient for you — we look forward to speaking with you soon!
Data Science 101
What is Data Science?
Data Science is the field focused on analyzing data and extracting insights through statistical analysis, machine learning, and data processing techniques. It combines aspects of mathematics, programming, and domain expertise to solve complex problems. A certification in Data Science can provide structured learning in these areas, introducing you to a comprehensive data science skill set.
Will a Data Science certification help my career path?
A Data Science certification demonstrates your commitment to learning and developing in-demand skills, which can make you stand out to employers. It can provide you with foundational knowledge, hands-on experience, and an overview of data science techniques that many hiring managers look for. A certification is also a quicker path than learning at your own pace and is a strong first step in building your career in data science.
Do I need a degree to become a Data Scientist?
While a degree in a relevant field can be beneficial, many successful data scientists have pursued alternative learning paths like certifications and bootcamps. Employers are increasingly focusing on skills and experience over formal education, especially in data science training programs. A Data Science certification can help showcase your knowledge and skills effectively.
How do I become a Data Scientist?
Becoming a Data Scientist typically involves learning data science techniques like analyzing data, machine learning, and programming, often through formal education, self-study, or certification programs. Practical experience with data projects and tools is also essential. A certification program can provide structured learning and projects to build your portfolio.
Data Scientists often start as Data Analysts or Junior Data Scientists and progress to Senior Data Scientist, Principal Data Scientist, or Data Science Manager roles. With experience, some move into specialized roles like Machine Learning Engineer or Data Engineer. Earning a certification can help you get started on this career ladder and prepare you for advancement.
What are the most in-demand Data Science jobs?
In-demand Data Science roles include Data Scientist, Machine Learning Engineer, Data Engineer, and Data Analyst. Companies seek professionals who can analyze data, build predictive models, and maintain data infrastructures. A Data Science certification, including Azure Data Scientist Associate, can help you prepare for these roles by providing core skills and knowledge.
What kinds of skills do I need to get a job in Data Science?
Key skills for Data Science roles include programming (typically Python or R), statistical analysis, analyzing data, machine learning, and data visualization. Familiarity with data tools like SQL, Pandas, and Scikit-learn is also valuable. A certification can provide hands-on experience with these tools, enhancing your job readiness and making data science methodology clearer.
Data Scientists use tools such as Python, R, SQL, and libraries like Pandas, Scikit-learn, and TensorFlow for machine learning and analyzing data. Tableau and libraries like Matplotlib and Seaborn are also popular to visualize data. A Data Science certification often covers these tools, preparing you for real-world projects and helping you understand data science methodology.
A Data Scientist typically focuses on building models and making predictions, while a Data Analyst works mainly on analyzing data to provide insights. Data Scientists often use machine learning and advanced statistical techniques, while Data Analysts focus on reporting and visualization. Certification in Data Science can help clarify these differences and build relevant skills in both areas.
What does a Data Scientist do?
A Data Scientist collects, processes, and analyzes data to derive actionable insights and build predictive models. They use data science techniques like statistical methods, programming, and machine learning to solve business problems. Certification in Data Science provides foundational knowledge and hands-on practice in these areas.
Data Science can be challenging as it involves math, programming, and analytical thinking, but it is accessible with dedicated learning. Many concepts build on each other, so a structured approach, like a data science training program, can make it easier to learn. With practice and persistence, anyone can build proficiency in Data Science.
Yes, Data Science is a high-demand, well-compensated field with diverse opportunities across industries. Companies rely on data science techniques to make informed decisions and innovate, creating many roles for skilled professionals. Earning a certification can open doors to entry-level positions and help advance your career.
How can a Data Science certification help my career?
A Data Science certification validates your skills, offers practical exposure to data science methodology, and provides hands-on experience with key tools, techniques, and data structures. It helps build a portfolio of projects to showcase to employers, making you more competitive in the job market. Certification can be a valuable stepping stone to achieving your career goals in Data Science.
How can data science help me if I don't want to become a Data Scientist?
Data science skills are valuable across many roles, helping professionals make data-driven decisions and uncover insights. Understanding data science methodology and concepts can improve your analytical skills, making you more effective in fields like marketing, finance, and operations. A certification in data science can broaden your skills and enhance your versatility in any industry.
How do I get a comprehensive Data Science background?
To build a comprehensive data science background, focus on learning foundational skills in programming, statistics, and machine learning, often available through certification programs or bootcamps. These programs typically provide hands-on projects to practice data science techniques in real-world settings. Certifications like Azure Data Scientist Associate can also provide targeted knowledge to strengthen your profile.
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Financing options
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