The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization. This specialization is presented for learners who want to start and complete the foundational part of the curriculum first, before moving onto the more advanced topics in Data Science: Statistics and Machine Learning.
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This course covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in Python, and conducting reproducible research.
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WHAT YOU WILL LEARN
Use Python to clean, analyze and visualize data.
Use GitHub to manage data science projects.
Learn how to ask the right questions, obtain data,
Set up Python, Github and other useful tools
SKILLS YOU WILL GAIN
Instructors
Ann-Marie Rice, Phd
Computer Science Professor
School of Computer Science
Mary Cobb
Computer Science Professor
School of Computer Science
Danyl Cano
Computer Science Professor
School of Computer Science
Syllabus
Module 1
4 Lectures
20:56
Week 1
Preview
10:53
Week 2
Preview
10:53
Week 3
10:53
Week 4
10:53
Module 2
4 Lectures
20:56
Week 1
Preview
00:53
Week 2
Preview
10:53
Week 3
10:53
Week 4
10:53
Module 3
4 Lectures
20:56
Week 1
Preview
00:53
Week 2
Preview
10:53
Week 3
10:53
Week 4
10:53
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.