For beginners or those seeking a refresher, 1 optional prep courses cover the fundamentals.
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DSS program: 11 total courses, 8 required to earn DSS certificate -
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Get full Data Science program, community & more with a CFI membership
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For teams of 2 or more learners
The Data Science Analyst Certificate Program at a Glance
CFI’s Data Science Analyst (DSA) Certificate Program equips you with practical, real-world data science skills, focused on data analysis in Python and R—as well as the building, evaluation, and interpretation of machine learning models using classification and regression. Take DSA Certification courses at your own pace, from anywhere and gain the skills and confidence to excel in high-paying careers as a Data Scientist, Data Analyst, or Financial Analyst.
Program Overview
11 courses
8 required courses
24 Hours
Average completion time
Receive a Certificate
To verify your skills
500,000+ 5-star ratings
Best-in-class training, as rated by you
Our Learners Work At:
Earning your Data Science Certificate
This specialization consists of hands-on courses delivering practical, real-world data science skills, focused on data analysis in Python and R—as well as the building, evaluation, and interpretation of machine learning models using classification and regression.
Core Courses
Complete 6 required core courses to build your skill set in Data Science Analyst Specialization.
Elective Courses
Choose a minimum of 2 electives (out of 4 available) to master more advanced topics and specialized areas.
Why Get A Data Science Certificate?
Data scientists earn $112K to $174K per year in the US (Glassdoor September 2023), 2.5 to 4 times higher than the average earnings in other fields. Moreover, Data Science is a rapidly growing profession, with thousands of new roles opening up each year (US Bureau of Labor Statistics).
Upon completion, you’ll receive a shareable blockchain digital certificate in Data Science. You can also order a physical certificate to be mailed to your door.
Data Science Analyst Certificate Skills & Learning Objectives
Predictive Analysis
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Learn common machine learning methods for making predictions
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Interpret and understand the results of machine learning models
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Examine key property valuation metrics and how they relate to the credit analysis process
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Model uncertainty using Monte Carlo simulation
Statistics
See DetailsCoding
See DetailsTaught by Industry Experts
Sebastian Taylor
Sebastian leads our BIDA® program, and has worked with a variety of BI tools across a number of industries. From quant energy risk management to financial and retail analysis, Seb loves the challenge of automating and communicating complex analysis with simplicity and clarity.
Andrew Russell
Andrew has extensive experience as a software engineer. His involvement in developing bespoke applications across many different organizations has led to expertise in a variety of programming languages and frameworks.
Joseph Yeates
Joseph is passionate about driving better decision making by creating, curating, and communicating insights from data. He has a degree in Business Administration and Finance, with further certifications in Business Analytics & Decision Making and Applied Database Administration & Design.
John Lee
John is an advocate of using analytics to drive decision making. He has a degree in Business Administration - Management Information Systems as well as a diploma in Data Science.
Lester Leong
Over the course of the years, Lester Leong has been applying data science and machine learning towards business and finance to improve profitability, efficiency, and model interpretability.
Explore Your Career Options with Data Science Certificate Program
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Data Analyst
Data Analysts analyze data from diverse sources, employing Business Intelligence and data science techniques to understand trends and performance. -
Data Science Analyst
Business Intelligence specialists excel in SQL, Data Visualization, and essential data science skills for tasks like forecasting and handling missing data. -
Finance Analyst
Successful finance analysts are skilled in data handling, collaborating with data scientists, and interpreting basic models effectively. -
Data Scientist
Data Scientists leverage Python, R, and SQL for intricate data analysis and predictive modeling.
What Our Students Say
The course provides a solid foundation in key concepts, techniques, and tools used in data science and machine learning, including statistical analysis, data visualization, regression, classification, and clustering algorithms.
Guy Adjokpota
Made me love Machine Learning so much more. Now I can kick start my career intent of developing skills in Finance Machine Learning! Thanks so much CFI.
Joshua Adesoji
I really enjoyed this course as a person with no coding background to really understand topics in Data Science and Machine learning.
Junho Kim
I love everything about the lessons, interactive exercises, and case demonstrations. It helps me deeply understand the topics.
