Course description
Applied Data Science with Python Specialization
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.
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Upcoming start dates
Suitability - Who should attend?
Some related experience required.
Outcome / Qualification etc.
What you will learn
- Conduct an inferential statistical analysis
- Discern whether a data visualization is good or bad
- Enhance a data analysis with applied machine learning
- Analyze the connectivity of a social network
Skills you will gain
- Text Mining
- Python Programming
- Pandas
- Matplotlib
- Numpy
- Data Cleansing
- Data Virtualization
- Data Visualization (DataViz)
- Machine Learning (ML) Algorithms
- Machine Learning
- Scikit-Learn
- Natural Language Toolkit (NLTK)
Training Course Content
- Introduction to Data Science in Python
- Applied Plotting, Charting & Data Representation in Python
- Applied Machine Learning in Python
- Applied Text Mining in Python
- Applied Social Network Analysis in Python
Course delivery details
This course is offered through University of Michigan, a partner institute of Coursera.
Suggested pace of 7 hours/week
Expenses
Please visit the Institute website for more information about tuition fees