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.
This Repository Contains the Material And Concepts Learnt In Specialization Course of Coursera
- 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
- 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
- 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)
University of Michigan The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
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