Packt Publishing
Python has grown into a key language that can be used to develop solutions for a variety of data science challenges. This course will teach you the fundamentals of data science using Python and its growing collection of libraries that focus on particular elements of data science.
In this course, we will get hands–on with a variety of data science tasks. After a quick primer on Python, you will start with a quick task: sourcing, processing, and cleaning a dataset. Then, you will use Python to mine data from its source and analyze available data via statistical and probability analysis techniques by using NumPy and pandas. You will also look at modeling data in order to perform Artificial Intelligence prediction by using the SciPy, scikit–learn, and statsmodels libraries. The course also covers visualization methods using the Matplotlib library to display this analysis and visually demonstrate patterns in the data.
By the end of this course, you will be able to work on data science tasks in a practical way with different Python libraries and achieve your goals.
About the Author
Nicolas Rangeon is a freelance data scientist. He has spent the last 2 years teaching data science, emphasizing how to store, retrieve, and analyze data from any kind of database. He developed a feel for teaching both technical skills and mathematical concepts; both are required if you want to be a proficient data analyst.
Instructor Details
Courses : 212
Specification: Fundamentals of Data Science with Python
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2 reviews for Fundamentals of Data Science with Python
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| Price | $9.99 |
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| Provider | |
| Duration | 2.5 hours |
| Year | 2020 |
| Level | Beginner |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$9.99
Rohit Kulkarni –
Instructor rushed through major concepts. No clear understanding on concepts.
Sandrine Demalt –
This course is good. The teacher explains very well the code and the theory. Despite a strong french accent, the diction is clear, dynamic and with a good rhythm (you won’t get bored!), so it was perfect for me, because I usually can’t stand listening to the same voice more than 20 minutes in a row. Pros and cons : +++ It’s possible to code from the 2nd video, and to do data science from the 2nd section +++ the mathematical concepts are very well explained for beginners (I with I had this math teacher at school !) ++ good rhythm in the narration ++ the concepts are very gradual + very good balance betwen theory and code + examples are interesting + we learn very quickly to analyse real world data quizzes are a bit too easy to really assess the level of students strong french accent I would say this course is perfect for beginners and average level students because it is short (2h30) , it isn’t rushed, and the progression is very gradual and goes very far : in 2h30 we go from a primer on python to Machine Learning ! It also fits if you want to learn the basics of Data Science without learning python.