Jupyter Notebook for Data Science

TDM Jupyter Notebook for Data Science 🛠️📊

Course Headline:

Collaborate, create interactive visualizations, and manipulate big data in the language of your choice.

Course Description:

🚀 Embark on a Data Science Adventure with Jupyter Notebook!

This comprehensive video course is designed to take you from novice to proficient in using Jupyter Notebook for a variety of data science tasks, focusing primarily on Python. Jupyter Notebook has established itself as the go-to platform for interactive data exploration and visualization among data scientists worldwide. It's not just a tool; it's a powerful environment that enables you to collaborate and communicate your findings in a clear and concise manner.

In this course, we will delve into the essentials of Jupyter Notebook, starting with basic data analysis tasks and gradually exploring more advanced features. You will become familiar with common scientific Python tools such as pandas for data manipulation, matplotlib for plotting static visualizations, and plotly for creating interactive visualizations.

Throughout the course, we'll put these skills into practice by working with real-world datasets, including crime and traffic accidents in New York City. We'll tackle common data science challenges like data scraping and cleaning, ensuring you gain hands-on experience in preparing data for analysis.

By the end of this journey, 🎓 You Will Be Able To:

• Navigate Jupyter Notebook interface with confidence
• Perform exploratory data analysis using pandas
• Create a wide range of static and interactive visualizations with matplotlib and plotly
• Handle real datasets and conduct your own data analysis from start to finish
• Share your findings through well-structured reports in Jupyter Notebook format
• Understand the power of collaborative environments for data science projects

This course is suitable for data science enthusiasts, analysts, and professionals who want to leverage the full potential of Jupyter Notebook. No prior experience with Jupyter Notebook or advanced Python knowledge is required, though a basic understanding of Python will be helpful.

📆 Course Version: The content in this course is based on Jupyter 5.4.1, which provides you with relevant and informative learning experiences regardless of the latest version's release.

About the Author: Dražen Lucanin

🧭 Dražen Lucanin is not just an instructor; he's a seasoned developer, data analyst, and the founder of Punk Rock Dev, an indie web development studio. With over a decade of professional experience in building web applications and performing data analysis using Python, JavaScript, and other technologies, Dražen brings a wealth of practical knowledge to this course.

🎓 His academic background is as impressive as his professional one – he completed a PhD in computer science at the Vienna University of Technology, where he researched energy efficiency in geographically distributed datacenters. His work on optimizing VM scheduling based on real-time electricity prices and weather conditions has contributed significantly to the field.

🔬 During his scientific pursuits, Dražen extensively used Python, Jupyter Notebook (formerly IPython Notebook), Matplotlib, and Pandas to manipulate and analyze various time series and spatial data datasets. He also delved into machine learning methods for financial crisis forecasting as an external associate at the Ruder Boškovic Institute.

🏫 A Master's degree in computer science from the University of Zagreb further solidifies Dražen's expertise, making him the perfect guide to navigate the intricacies of Jupyter Notebook for Data Science. With his guidance, you'll unlock the potential of this powerful tool and enhance your data science skillset.

Enroll now and transform the way you approach data science with Jupyter Notebook! 🌟