IT : Python | Fundamentals Of Data Science With Python
Coding, Online python programming compiler, Python courses near me, Python programming language
Simpliv LLC
Summary
- Certificate of completion - Free
- Tutor is available to students
Overview
What will you learn
Use Python for data mining, loading, and manipulation
Understand simple statistics and probability using NumPy
Work with Bayesian statistical analysis with NumPy library
Perform statistical modeling and fitting using the NumPy, SciPy, and statsmodels libraries
Use Python's graphics libraries to plot data with the Matplotlib library
Work with the scikit-learn library to build AI models
Description
Description
Implement powerful data science techniques with Python using NumPy, SciPy, Matplotlib, and scikit-learn
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.
After having graduated with a Masters degree in Computer Science, Nicolas worked as a freelance data scientist and data engineer for several small businesses where he deployed, managed, and mined databases in order to get value from their stored data.
When it comes to deploying and managing a relational database, his first choice is always PostgreSQL, due to its robustness and its ability to handle large amounts of data efficiently.
Basic knowledge
The course begins with a primer to Python, so you don’t have to worry if you haven’t worked with Python before
Who is this course for?
Who this course is for:
This course is for aspiring data scientists who are eager to add this skill to their toolkit, as well as those who are required to work on data science projects using Python.
Questions and answers
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Certificates
Certificate of completion
Digital certificate - Included
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Legal information
This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
