Explore data science fundamentals, including generative AI, time series, and business analytics. Gain insights into practical applications using Python libraries like pandas, seaborn, and TensorFlow.
4.3
14 Lessons
2h 30min
Updated 1 month ago
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- An understanding of the fundamentals of data science for data-driven decision-making
- Working knowledge of practical applications of data science in industries and daily lives
- Knowledge of career paths in data science for today’s world
- Familiarity with some famous technologies and tools used in data science
- A mastery of how the data science pipeline works with some hands-on experience
Learning Roadmap
1.
Introduction to Data Science
Introduction to Data Science
Get familiar with data science fundamentals, industry applications, and its evolving role.
2.
Fundamentals of Data Science
Fundamentals of Data Science
Unpack the core of data science pillars, distinctions from machine learning, and essential tools.
3.
Applications and Careers in Data Science
Applications and Careers in Data Science
3 Lessons
3 Lessons
Work your way through data science applications, roles, and specialized topics.
4.
Mastering Data Science
Mastering Data Science
5 Lessons
5 Lessons
Find out about visualizing, processing, modeling, and presenting data for effective analysis.
Certificate of Completion
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Developed by MAANG Engineers
ABOUT THIS COURSE
Data science extracts meaningful insights from the data for data-driven decision-making. This course is designed to provide an insight into the fascinating world of data science, whether you are a beginner or want to move your career forward in data science.
We start the course by covering the fundamentals of data science and the usage of data science in big tech industries and real-world applications. We discuss its specialized applications in generative AI, time series analysis, business analytics, and the different career paths in data science. Lastly, we cover an example with various Python libraries, including pandas, seaborn, scikit-learn, and TensorFlow. We use pandas and seaborn for basic data processing and data visualization and scikit-learn and TensorFlow for modeling and analysis.
With the completion of this course, you’ll emerge with a concise yet comprehensive knowledge of data science and the required skills to enhance your data science knowledge for data-driven decision-making.
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