What you will learn
- Learn about various tools used by Data Scientists and become experienced in using some of them like Jupyter notebooks.
- Develop an understanding of the key steps involved in tackling a data science problem.
- Learn to follow a methodology to think and work like a Data Scientist.
- Write SQL to query databases and explore relational database concepts.
- Complete hands-on labs and projects to apply their newly acquired skills and knowledge.
Data science and machine learning skills continue to be in highest demand across industries, and the need for data practitioners is booming. Upon completing this Professional Certificate program, you will be armed with the basics to jump start your career in data science and machine learning.
It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. Anyone with some computer skills and a passion for self-learning can succeed as we start small and build up to more complex problems and topics.
When you are ready you can build up to more complex topics in our full 9-course Data Science Professional Certificate program which covers a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, machine learning, and a capstone project.
With the tremendous need for data science and data analyst professionals in the market today, this program will kick-start your path in data science and arm you with the fundamentals of Data Science so that you have the confidence to take the plunge and start your data science career today.
Courses in this program
IBM's Data Science Foundations Professional Certificate
- 3–6 hours per week, for 6 weeks
Learn about the world of data science first-hand from real data scientists.
- 3–7 hours per week, for 7 weeks
Learn about the most popular data science tools, including how to use them and what their features are.
- 3–7 hours per week, for 7 weeks
Learn about the methodology, practices and requirements behind data science to better understand how to problem solve with data and ensure data is relevant and properly manipulated to address a variety of real-world projects and business scenarios.
- 2–4 hours per week, for 4 weeks
Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field.
- Over 2.5 million jobs in data science and related professions (Burning Glass)
- Python most popular language for data science (KDnuggets)
- Data Science and Analytics professionals have average starting salary of over $80,000 in the US.
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