Coursera Applied Data Science with Python Specialization Review from the University of Michigan in 2023
The online course offers Applied Data Science with Python Specialization Certificate/certification for those who have basic about programming and will be able to complete this course successfully.
Applied Data Science with Python Course refers to an intermediate-level specialization.
Coursera Applied Data Science with Python Specialization Review in 2023
Applied Data Science with the python University of Michigan, launched this excellent specialization focused on the applied side of data science.
You will certainly get a strong introduction to commonly used data science Python libraries, like matplotlib, pandas, nltk, scikit-learn, and networkx, and you can learn how to use them on real data.
This online specialization is a series of five courses, each course is focused on the use of one or more free Python libraries. The courses and the libraries covered by each area:
- Introduction to Data Science in Python: NumPy, SciPy, and Pandas
- Applied Plotting, Charting, & Data Representation in Python: Matplotlib and seaborn
- The Applied Machine Learning in Python: scikit-learn
- Applied Text Mining in Python: NLTK and Gensim
- Applied Social Network Analysis in Python: NetworkX
You can easily gain your skills in those areas that are required to initially establish your knowledge of programming. These courses are built fand ocuses on some aspects of using Python for data-science applications.
You will be Going to Learn from This Specialization
- 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
Rating: 4.5 out of 5
Enrollment: 150k+ learners
This Specialization was designed as
a: Data Science in Python
b: Applied Plotting, Charting & Data Representation in Python
c: Applied Machine Learning in Python
d: Applied Text Mining in Python
e: Applied Social Network Analysis in Python
This should be taken in order and before any other course in the specialization. After completing courses 1 to 3, courses 4 and 5 can be taken in any order.
The Courses will Cover Accordingly
1st-course Introduction to Data Science in Python refers to fundamental Python programming techniques such as lambdas, reading and manipulating CSV files, and the NumPy library.
Then Applied Plotting, Charting, & Data Representation in Python will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library.
It began by touching on what makes a good and bad visualization, and what statistical measures translate into terms of visualizations.
Then gradually moves to the technology used to make visualizations in python to a discussion of other forms of structuring and visualizing data.
After that, Applied Machine Learning in Python comes with applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods.
This course refers to supervised (classification) and unsupervised (clustering) techniques used for a particular dataset and need, engineering features to meet that need, and writing Python code to carry out an analysis.
By finishing 3 courses Applied Text Mining in Python can be learned, where the learner will be introduced to text mining and text manipulation basics.
Finally Applied Social Network Analysis in Python introduce the learner to network analysis through tutorials using the NetworkX library for covering models of network generation and the link prediction problem.
Process of Taking The Course
There will be programming assignments that are very effective for understanding and applying Python.
The specialization includes a hands-on project. You’ll need to finish the project(s) successfully to complete the Specialization and earn your certificate.
Why This Specialization titled “Applied”
The word “Applied” in the specialization and course titles, there is not much theory presented in these courses, just enough theory to understand the exercises.
- Research Assistant Professor Christopher Brooks, University of Michigan is the mentor of the first two courses, Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation.
- Christopher Brooks, Assistant Professor, University of Michigan
- V. G. Vinod Vydiswaran, Assistant Professor, University of Michigan takes Applied Text Mining in Python.
- Kevyn Collins-Thompson, Assistant Professor, University of Michigan takes Applied Machine Learning in Python.
- Daniel Romero, Assistant Professor, University of Michigan takes Applied Social Network Analysis in Python.
Earn Certificate for Career
Nowadays python becomes one of the dedicated programming languages for developing new systems Many jobs are looking for people who know python.
Applied Data Science with python will give you extraordinary values if you rant to start your career in programming. This course can be added extra credit to your CV.
After finishing courses and completing the hands-on project, you’ll earn a Certificate from the specialization, Applied Data Science with Python Certification, at the University of Michigan that you can share with prospective employers and your professional network.
Career in Applied Data Science
Applied Data Science is one of the most highly paid jobs nowadays. A Data Scientist is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data.
You can easily start your career in Data Science with python after completing this online specialization if you want to be a Data Scientist. Some of the prominent Data Scientist job titles that you desire:
- Data Architect.
- Business Intelligence Manager.
- Data Administrator.
- Business Analyst.
- Analytics Manager.
- Data Analyst.
Coursera Easy Subscription
After you subscribe to a course that is part of a Specialization, you will be automatically subscribed to the full online Specialization.
It’s okay to complete just one course you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, there will be no refunds, but you can cancel your subscription at any time for $49/month (for certificate and graded materials) to continue learning after the trial free ends.
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