Python for Data Science: Master NumPy & Pandas on Real Data
What you'll learn
- Learn Python for Data Science
- Master the Pandas data structures Series and DataFrames
- Master the NumPy Array and understand the strength of it
- The full Data Science process. Collect data, clean data, combine data, enrich data, model data, and visualize data.
- How to make simple and efficient Data Analysis
- Use the libraries of Pandas and know how to explore it further
- Understand the difference between NumPy and Pandas
- Master the built in Data Structures in Python and understand their strengths
- Built projects from external sources like CSV files
- Combine datasets to enrich the value of Data Science projects
- Master vectorizations and understand the power of it
Course content
- Preview03:13
- Preview02:11
- Preview03:50
- Preview02:22
- Preview05:19
Requirements
- Very basic Python skills - understand integers, floats, strings, for-loop
- Simple math operations and basic percentage knowledge
Description
Data Science is an Interdisciplinary area that can seem overwhelming to master. It is in the field between Math, Statistics, Programming, Visualization, Machine Learning, among things.
This course will show you that with limited set of techniques you can make amazing results.
Not only does this course try to get you kickstarted with Data Science concepts, it has focus on delivering it the best way for you to remember and apply it later.
This course is focused on explaining and applying complicated concepts in an easy way to make your learning journey as smooth as possible.
Starting Data Science with NumPy and Pandas in Python can be overwhelming.
Data structures with endless functionality.
Large and complex libraries.
...and at first, difficult syntax to understand.
This course focuses on to get you a solid foundation that will enable you to create Data Science projects on your own.
Most courses focuses on covering a broad basis, with the result that leaves the student overwhelmed and confused with too much information. This course focuses on a solid basis that you will master after completion.
Learning approach of this course
Master a small basis to get full power with Python built-in data structures, NumPy, and Pandas to make real Data Science project.
Work on real life examples with real datasets.
Make real projects in Python built-in data structures, NumPy arrays, and Pandas Series and DataFrames to understand to true power of each.
Keep incremental learning cycles small to ensure you master each step.
All datasets and source code available in the course and you will do all the coding along.
Wrong approach to learning
Most tutorials and courses are focused on covering the broad basis of Pandas, NumPy, or Python data strctures.
Too much focus on covering all the all awesome functionalities and syntax.
No real examples or too tailored to be used in real life.
Not enough coding included to really understand it.
Approach with Python
The simple coding exercises will be done in the Udemy platform.
More advanced will be done in your own environment.
You can use PyCharm (the best Integrated Development Environment (IDE) for Python and it is FREE) or another strong IDE. You can also use Jupyter Notebook.
What will we cover in this course?
Python built-in data structures with real life examples.
Learn the power of Python lists.
How read CSV files with datasets and explore the datasets, done on real life dataset.
Understand and use Python dictionaries to master the power of them.
Master the NumPy array to understand the power and limitations compared to Python lists and dictionaries.
Understand and master the power of vectorization with NumPy.
Work like a Data Scientist with NumPy: Load the data, understand the data, clean the data, enrich the data, explore the data, visualize the data.
Making real project with NumPy on real life large datasets.
Creating plots and fitting lines to data points.
Pandas compared to NumPy. When to use what?
Understand the data structures of Pandas: Series and DataFrames.
Master the power of vectorization with Pandas.
Use Pandas on large real life datasets.
How to combine (merge and join) datasets from different sources.
Dealing with missing data points.
Cleaning data.
Convert data to the datatype needed and dealing with errors.
Visualize data on world maps.
Calculate new data.
Test hypothesis of data from real sources.
How to continue your journey as a Data Scientiest.
You code along - you only learn by trying yourself - 50+ coding exercises
At each step you make the implementation along with me.
You implement it on all stages to increase your understanding of security
Basically, we learn along the way with more than 50+ coding exercises.
What is needed to fully understand this course?
You should have a basic understanding of Python.
Understand basic math from elementary school level.
Who is this course for?
You want to learn and understand the Data Science process.
Want to master NumPy and Pandas like a professional.
Those who want to try it with programming examples to fully understand the depth of each lesson
All questions posted in the course will be answered within a day and in most cases within an hour. We strive to give you the best experience to kick-start your journey.
The course has a 30 day money back guarantee that ensures if you are not satisfied, you will get your money back. Feel free to contact me directly if you have any questions.
Who this course is for:
- Students that want to get started using Pandas and NumPy data structures
- Students that start their Data Science journey and need the foundation
- Curious Data Science student that want to have a programmatic approach to Data Science
Instructor
![Rune Thomsen](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.7 Instructor Rating
- 370 Reviews
- 16,933 Students
- 7 Courses
Hi, I'm Rune.
Thank you for checking my course.
With a PhD in Computer Science, an MBA to learn business administration and finance, 10+ years in professional software development, I still find my greatest passion in teaching.
I have helped students succeed with programming since I took my PhD in computer science and was teaching at Aarhus University, Denmark.
Since then, I was a software engineer (programmer), the head of branch of developers, build big software solutions, and software engineering manager in a software as a service (SaaS) company.
Along that journey, I took an MBA from Henley Business School in UK to learn about business administration and finance.
My journey on Udemy started in 2020 and the focus has been on Python programming, which is my greatest passion. I love to make concepts easy to understand and fun to learn.
Until now I have the Udemy Bestseller:
Master Modern Security and Cryptography by Coding in Python
I started to program as 12 years old before the internet was available for common people (read: for me).
It was Basic, yes the language Basic with line numbers.
My best friend started and we helped each other to get better. Before I reached college, I had helped many friends with programming.
It was natural for me to teach at college and I missed it when I left after teaching all the fundamental programming and computer theory courses at least once.
Later I have helped new employees to program, as well as other professionals to automate their work with Python.
I have helped a guy with no experience in programming to get his first job within 6 months of starting.
If anything, please feel free to reach out to me and I'll be there for you every step of the way.
Rune