Data Analysis with Python: Part 3 of 6 Numerical Computing with Numpy (Live Course)



“Data Analysis with Python: Zero to Pandas” is a practical, beginner-friendly and coding-focused introduction to data analysis covering the basics of Python, Numpy, Pandas, data visualization and exploratory data analysis. You can learn more and register for a Certificate of Accomplishment at http://zerotopandas.com ⭐️ Resources ⭐️
🔗 Numerical computing with Numpy: https://jovian.ml/aakashns/python-numerical-computing-with-numpy
🔗 100 Numpy exercises: https://jovian.ml/aakashns/100-numpy-exercises
🔗 Numpy array operations assignment: https://jovian.ml/learn/data-analysis-with-python-zero-to-pandas/assignment/assignment-2-numpy-array-operations
🔗 Discussion forum: https://jovian.ml/forum/t/lecture-3-numerical-computing-with-python-numpy/10593 ⭐️ Topics covered ⭐️
⌨️ Going from Python lists to Numpy arrays
⌨️ Working with multi-dimensional arrays
⌨️ Array operations, slicing and broadcasting
⌨️ Working with CSV data files 🎥 Watch the entire series here: https://www.youtube.com/playlist?list=PLWKjhJtqVAblvI1i46ScbKV2jH1gdL7VQ ✏️This course is taught by Aakash N S, cofounder & CEO of Jovian.ml – a platform for sharing, showcasing and collaborating on data science projects online
🔗 YouTube: https://youtube.com/jovianml
🔗 Twitter: https://twitter.com/jovianml 🔗 LinkedIn: https://linkedin.com/company/jovianml — Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp

Data Analysis with Python: Part 3 of 6 Numerical Computing with Numpy (Live Course)

Data Analysis with Python: Part 3 of 6 Numerical Computing with Numpy (Live Course)

 

 

 

 

 

 

 

 

 

Contact us

More Data Analysis with Python: Part 3 of 6 Numerical Computing with Numpy (Live Course) Videos

Leave a Reply

Your email address will not be published. Required fields are marked *