Brief Introduction
Develop your data science and analytics skills and improve your understanding of using data in the workplace.Course Summary
This course is designed to teach you the practical skills you need to become a data scientist. You’ll learn how to clean, analyze, and interpret data using Python and other tools, and you’ll be introduced to the fundamentals of machine learning and statistical modeling.Key Learning Points
- Learn how to clean, analyze, and interpret data using Python and other tools
- Get introduced to the fundamentals of machine learning and statistical modeling
- Gain practical skills to become a data scientist
Related Topics for further study
Learning Outcomes
- Develop practical skills in data science
- Apply data analysis techniques to real-world problems
- Become proficient in Python programming
Prerequisites or good to have knowledge before taking this course
- Some prior programming experience in Python
- Familiarity with basic statistical concepts
Course Difficulty Level
IntermediateCourse Format
- Self-paced
- Online
Similar Courses
- Data Analytics for Business
- Introduction to Data Science
- Applied Artificial Intelligence
Related Education Paths
- Data Science Certification Program
- Machine Learning Engineer Certification Program
- Business Analytics Certification Program
Related Books
Requirements
- This course is for anyone who’d like to learn more about data science. The course will be useful for students, novice programmers, and any professionals who interact with data. For professionals or students who are new to the subject, the course will provide a foundation for advancing your career using data science and data analytics skills. For those already working in the IT industry, you’ll have the opportunity to strengthen and develop your knowledge and expertise in the area of data analytics and, more generally, data science. There are no programming prerequisites for students taking this module, but you should have a basic understanding of mathematical thinking and elementary statistics.
Knowledge
- The terminology used in the data science sectorCurve fitting and plotting of statistical distributionsVisualisation techniquesMaking use of geolocation dataClassification and clusteringFeature extractionClustering textSupervised and unsupervised learningApplication of machine learning to text and images
Summary of User Reviews
The Applied Data Science course on FutureLearn has received positive reviews from many users. The course covers various topics related to data science and provides hands-on experience through practical assignments. One key aspect that many users found good is the interactive nature of the course and the availability of expert instructors. However, some users have mentioned the pace of the course being too fast as a major drawback. Overall, the course has received positive feedback from users.Pros from User Reviews
- Interactive and engaging course material
- Expert instructors available to provide guidance
- Practical assignments provide hands-on experience
- Covers a wide range of topics related to data science
Cons from User Reviews
- Pace of the course can be too fast for some users
- Some users found the course material to be too basic
- Limited scope for advanced learners
- No certification provided upon completion of the course
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