Data scientist course

Data Science Data Scientists try to make sense of the data that’s all around us. Taking a data science course can help you make informed decisions, create beautiful visualizations, and even try to predict future events through Machine Learning. If you’re curious about what you can learn about the world using the data produced every day, then data science might be for you!

Master's Program 79691 Ratings Ranked #1 Ranked #1 Data Science Course by This IBM-sponsored Data Science course includes unique hackathons, masterclasses, webinars, and Ask-Me-Anything sessions. The online training will give you hands-on experience with R, Python, Machine Learning, Tableau, Hadoop, and Spark. Improve your knowledge with this Data Science course and live interaction with other practitioners and Machine Learning Engineers. • Add the IBM Advantage to your LearningExclusive Hackathons, Masterclasses and Ask-Me-Anything sessions by IBM • Capstone and 25+ Data Science ProjectsIndustry relevant projects from the likes of Amazon, Walmart, Mercedes Benz, and many more • Immersive Learning Experience8X higher live interaction in live Data Science online classes by industry experts • Applied Learning PedagogyTop notch Data Science course curriculum with integrated labs and hands-on experience This Data Science course, in collaboration with IBM, accelerates your career in Data Science and provides you with the world-class training and skills required to become successful in this field. This course offers extensive training on the most in-demand Data Science and Machine Learning skills with hands-on exposure to key tools and technologies, including Python, R, Tableau, and concepts of Machine Learning. Become a Data Scientist by diving deep into the nuances of data interpretation, mastering technologies like Machine Learning, and mastering powerful programming skills t...

What You'll Learn What is data science, and how can it help you make sense of the infinite data, metrics, and tools that are available today? Data science is at the core of any growing modern business, from health care to government to advertising and more. Insights gathered from data science collection and analysis practices have the potential to increase quality, effectiveness, and efficiency of work output in professional and personal situations. Data Science Principles makes the foundational topics in data science approachable and relevant by using real-world examples that prompt you to think critically about applying these understandings to your workplace. Get an overview of data science with a nearly code- and math-free introduction to prediction, causality, visualization, data wrangling, privacy, and ethics. Data Science Principles is an introduction to data science course for anyone who wants to positively impact outcomes and understand insights from their company’s data collection and analysis efforts. This online certificate course will prepare you to speak the language of data science and contribute to data-oriented discussions within your company and daily life. This is a course for beginners and managers to better understand what data science is and how to work with data scientists. Data Science Principles is part of our Harvard on Digital Learning Path. The Harvard on Digital course series provides the frameworks and methodologies to turn data into insight, t...

A subfield of computer science, data science is the study of large quantities of data. A relatively new and quickly growing field, data science offers excellent career opportunities. This page explains how to become a data scientist. We cover experience and education requirements, look at certifications and job search strategies, and outline the steps to become a data scientist. What Education Do Data Scientists Need? Education requirements for data science professionals vary by position, employer, and industry. Data scientists typically need at least a Data analysts and data engineers usually need a bachelor's degree. Becoming a data scientist or computer and information research scientist usually requires a master's. Some data science professionals hold a mix of education levels. For example, someone might earn a bachelor's in computer science and complete a In general, career opportunities and salaries increase as people earn higher degree levels. A graduate degree can also help job applicants stand out from candidates with just a bachelor's. Requirements to Become a Data Scientist There is more than one way to enter the data science field. Data scientist requirements differ by employer, industry, and location. Aspiring professionals can meet data scientist job requirements in various ways. The typical process to become a data scientist includes at least a four-year college degree in computer science, data science, or a related field. Many data scientists also pursue gr...

Learn to make data-driven decisions through this acclaimed bootcamp that delivers a high-engagement learning experience, leveraging Caltech’s academic excellence in data science. Learn to make data-driven decisions through this acclaimed bootcamp that delivers a high-engagement learning experience, leveraging Caltech’s academic... • Caltech CTME A leading science and engineering institute known for industry-pioneering innovations Caltech’s contributions have earned international recognition & 38 Nobel Prizes • Learn from Great Educators Global Data Science experts lead training with industry-specific cases and applications Masterclasses delivered by distinguished Caltech instructors • Experiential Learning in a Cohort-based Bootcamp 6 months of applied learning: 25+ hands-on projects with integrated labs Weekly hands-on project sessions to elevate your data science skills This Data Science Bootcamp starts with statistics and data science as a whole. In this course, you will learn how to define statistics and essential related terms, explain central tendency and dispersion measures, and comprehend skewness, correlation, regression, and distribution. The boot camp also covers programming basics, Python programming, Python installation and environments, and the different functions of Python. • This Data Science Bootcamp will establish your mastery of data science and analytics techniques using Python. In this bootcamp, you’ll learn the essential Python libraries required for ...

What You'll Learn The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio. In each course, we use motivating case studies, ask specific questions, and learn by answering these through data analysis. Case studies include: Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team (inspired by Moneyball), and Movie Recommendation Systems. Throughout the program, we will be using the R software environment. You will learn R, statistical concepts, and data analysis techniques simultaneously. We believe that you can better retain R knowledge when you learn how to solve a specific problem. The course will be delivered via Professor of Biostatistics, T.H. Chan School of Public Health Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute. For the past 15 years, Dr. Irizarry’s research has focused on the analysis of genomics data. During this time, he has also taught several classes, all related to applied statistics. Dr. Irizarry is one of the founders of the Bioconductor Project, ...