Start Your Data Science Career Here
"Amazing Course! I am learning Numpy & Pandas for the first time and this course taught me a lot!" - Jyotish G.
Why this is the best learning approach?
Perhaps you have never thought about it...
...but a university education focuses on the following.
- It teaches you all aspects of the theory.
- It covers all possible technologies for any edge case.
- Try every method you can come across.
At the end of the day, you're a generalist who still needs to pull it all together yourself to create valuable data science projects.
Most online courses copy this learning approach which leaves you more confused with all the options at the end.
This course is different
The core focus of this course is.
- To equip you with the critical elements to create valuable projects.
- Narrow down what is necessary for initial success.
- Teach you to work with data with Python, the core competency of a data scientist.
At the end of this course, you will be equipped with a toolbox to create valuable data science projects.
Create Full Data Science Projects
The key to initial success is by mastering the critical elements - not the most tools and technologies.
Minimum Basis - Full Power
Master the critical elements to create successful Data Science Projects. To initially succeed you need to focus in-depth on what matters.
Q&A
You can ask the instructor, Rune, questions directly and get answers to your challenges.
Downloadable Cheat Sheets
What did you learn? Download Cheat Sheets for JuPyter Notebook shortcuts, Python learnings, and more.
Curriculum
- Introduction to Notebook 01 (1:59)
- What is a CSV file?
- Import CSV file to Python List (7:23)
- Convert Column to float (3:00)
- Send functions as argument
- Sort using a user defined function (3:27)
- What is a lambda function?
- Sort using a lambda function (3:26)
- Python Slicing Cheat Sheet (2:00)
- Slicing Python Lists (2:43)
- Understand List of Lists (3:04)
- List of LIsts (3:36)
- Wrap up Notebook 01 (1:20)
- Introduction to Notebook 02 (1:22)
- Read CSV file into List of Dicts (3:53)
- Sort using a user defined function (3:09)
- Sort using a lambda function (1:49)
- Remove items from List of Dicts (3:37)
- What is List Comprehension
- Remove items using List comprehension (2:21)
- Extract columns of data from a List of Dicts (3:27)
- Plot data on chart (2:52)
- Wrap up Notebook 02 (1:42)
- Introduction to project (0:45)
- Introduction to datasets (3:30)
- Load data into correct data type using NumPy (4:10)
- Overview of Introvert and Extrovert (6:19)
- Average time elapsed on questions (5:54)
- The 5 fastest and 5 slowest replies (3:39)
- NumPy filtering (1:42)
- Change wrong data points (6:05)
- Introvert and extrovert data split (1:29)
- Average age for introverts and extroverts (1:12)
- Lowest and highest rated questions (4:30)
- Plot length of questions vs average response time (2:10)
- Fitting plot to a straight line (2:02)
- Wrap up Notebook 05 (2:52)
- Introduction to pandas (6:18)
- How pandas differ from NumPy (6:07)
- Introduction to Series (2:08)
- Our first Series (3:33)
- Vectorize with Series (2:27)
- Indexing in a Series (4:27)
- Introduction to DataFrames (3:01)
- Our first DataFrame (3:00)
- Indexing our DataFrame (2:36)
- Use loc and iloc (2:52)
- Adding columns to our DataFrame (3:41)
- Wrap up Notebooks 06 and 07 (1:51)
- pandas Cheat Sheet (1:58)
- The 5 Steps of Data Science (4:03)
- Inspect the GDP data and load the CSV file (5:49)
- Enrich the data with Growth rate (4:55)
- What is a View in a DataFrame
- Create a view of growth rate data (2:05)
- Dealing with NaN (data cleaning) (1:42)
- Using Geopandas (1:57)
- Understand the challenge to combine data (5:02)
- Merge the data (2:06)
- Visualize the data (1:22)
- What is log-scale and why use it?
- Adding loc-scale and a legend (6:56)
- Calculate and visualize growth per capita (2:58)
- Wrap up Notebook 08 (2:36)
You get access to Python Circle
When you join the Python Circle community, you will:
Have access to private community events where I will share knowledge and experience on how to succeed in your career faster and secure yourself a bright future.
Have exposure to new ideas, technologies, and approaches in Python development that will make you more desirable to any business.
Have access to unreleased Python resources that will provide you with additional insight into Python and how to succeed faster.
...but most importantly, you will connect with other Python learners. Collaborating with other will improve your skill drastically.
Be part of something bigger!
Hi, I am Rune
I have turned my passion for programming and teaching into several successful online courses and have an engaging social following.
In this course, I share with you my years of experience helping people succeed with Data Science.
- Focus on a minimal basis with full power.
- Create full projects.
- Keep it simple.
- Use efficient technologies.
- Follow best practices.
Testimonials
"Thorough explanations making difficult concepts understandable." - Matthew P.
"Amazing Course! I am learning Numpy & Pandas for the first time and this course taught me a lot!" - Jyotish G.
"Course objective is to learn the critical basics to quickly develop useful codes for data science is exactly what I am looking for." - Abdol S.
"It seems very good starting point." - Sumaya A.
"Most enjoyable, and enlightening!" - Charles D. R.
"Great course, we are not only coding along with Rune, but he gave some professional advises, like I think every think he goes to the documentation and show how to read it and how to use it. Rune is a great instructor, he has a big enthousiasm in his video, it seems he really enjoy teaching and helping students. He always answered my questions, with many details, and in most cases in less than 30 minutes (I think in the others cases he's probably sleeping :) )" - Adel N.
"Just Started, liked the beginning" - Javed B.