If you are thinking of joining Data Science with Python Specialization on Coursera but thinking about whether it's worth your time and money, you have come to the right place. Earlier, I have shared the best Coursera courses for Data Science, and today, I will review one of the most popular Data Science specializations on Coursera. If you have been learning online, then you may know that Coursera is one of the giant platforms out there that offers courses in many different industries, from web development and IoT to business and self-development, and all those courses are created by major universities such as Michigan University and some companies like IBM which means you are in good hands when enrolling in some of their courses.
The platform contains what’s known as a specialization which is a huge program that contains many small courses in a certain industry, and some of these specializations get viral with hundreds of thousands of enrollment and big rating scores, and Applied Data Science with Python Specialization is one of them.
In today's article, you will explore this specialization, where it is important to take it, who is the instructor of this massive program, and whether it is worth enrolling and paying for this data science specialization.
Review of Applied Data Science with Python Specialization Coursera Course in 2024
1. The Instructors Reputation
The course is reached by four instructors. Let’s start with the first one named Christopher Brooks, an assistant professor at Michigan University, and the second one named Kevyn Collins, an associate professor at Michigan University.The other two instructors are also assistant professors at the Michigan university Daniel Romero and his research in theoretical analysis related to social and information networks. The other is Vinod Vydiswaran in natural language processing and data mining.
2. The Specialization Content
The specialization contains five courses focused on learning python and then applying data science techniques using this programming language and some machine learning algorithms. So let’s start exploring what this course offers to learners:2.1. Introduction to Data Science in Python
Since this course applies data science using python, it makes sense to start first exploring this language, and this course is all about learning the python fundamentals such as lambda function reading files and CSV data manipulation, as well as some libraries such as NumPy for mathematical calculation and pandas for importing CSV files and reading data.2.2. Applied Plotting, Charting & Data Representation in Python
After learning the fundamentals of python and how to process data, it's time to start making some visualization and take insight from your data. This course is all about that, and you will use libraries like matplotlib and seaborn to make plotting and charts and some terms on when you use the different kinds of visualization graphs and more.2.3. Applied Machine Learning in Python
This course is about machine learning and specifically supervised learning techniques using the Scikit-Learn library. You will start with the fundamentals of this technology using the Sckikit-Learn library and classification model, then move to supervised learning and some terms like logistic regression and support vector machine, evaluate your ML model, and much more.2.4. Applied Text Mining in Python
This course is for people who want to know how machines like Siri or Google assistants understand the human language and reply to them with the appropriate answer. You will learn text mining and the basics of natural language processing and use the NLTK library for this purpose and text classification and topic modeling.2.5. Applied Social Network Analysis in Python
This course will be about learning social network analysis using the NetworkX library. You’ll start by learning the different types o networks, then analyze the connectivity them based on many factors such as distance and reachability, and deep dive into measuring the importance of a node in a certain network and the network evolution.3. People Review
The course has got more than 200k enrollment with a score rating of 4.5 out of 5, which is considered a great rating score, and the course has great video productions as well as many quizzes to test your knowledge throughout the specialization, and the language that used is python which is very friendly for people who never coded before.If you do more research on people's review sites like Reddit or Quora, you will see that most people recommend taking this specialization rather than many other classes on the internet since it starts as a beginner to be advanced in data science.
- Top 10 Courses Courses for Programmers in 2024
- Top 10 Coursera Projects for Programmers and Developers
- Top 10 Coursera Certifications to start your career
- 7 Best courses to learn Artificial Intelligence in 2024
- Udemy vs Pluralsight? Which is a better learning platform?
- 10 Best Coursera Courses to learn Cloud Computing
- Coursera Plus Review - A better way to learn on Coursera
- Top 10 Coursera Courses to learn Web Development
- Top 10 Coursera Courses to learn Data Science
- 18 Coursera Courses to learn from top Tech Companies like Google and IBM
- Top 5 Computer Science Degrees you can join online on Coursera
- Udemy vs Coursera? which is better to learn Tech and Programming
- Do Coursera Certificates help in Job and Career?
- Udemy vs Educative vs CodeCademy? Which is better for beginners
- 10 Coursera Specialization and Certifications to learn Python
- 5 Best Coursera Professional Certificates for Programmers
- 8 Projects You can do to learn Python in 2024
- 5 Data Science degrees you can earn on Coursera Online
- 10 Data Science and Machine Learning Certifications form Coursera
Thanks for reading this article. If you like this review of Coursera's Applied Data Science with Python Specialization, then please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.
No comments:
Post a Comment