- Course type
- Paid course
- 4 hours
- 42 lessons
- Available on completion
- Course author
- Idan Gabrieli
- Python for Data Science and Machine Learning Projects
- Learn to use the Pandas Data Science Library
- JupyterLab Development tool
- Develop Jupyter Notebooks
- Loading and Analysing Tabular Datasets
- Selecting, Filtering, and Cleaning Data
- Grouping, Sorting, and Exporting Data
********* Feedback from Students ************
Excellent course, allows you to go step by step and get to know the bookcase, direct to the point thank you for such good teaching Jesus David
I am currently new in data science, I knew Python language and Competitive programming after that I was waiting to learn data science by myself. This course really very helpful for me to learn new things and data science and machine learning. I am really waiting for this new part (Level 3). Animesh K.
A fantastic course for getting the knowledge of pandas in depth along with ML applications. This is what I am searching for. It had better if it has some more quiz questions to test our skills and understanding. Enjoyed a lot. Anshika Verma
Unleash the Power of ML
Machine Learning is one of the most exciting fields in the hi-tech industry, gaining momentum in various applications. Companies are looking for data scientists, data engineers, and ML experts to develop products, features, and projects that will help them unleash the power of machine learning. As a result, a data scientist is one of the top ten wanted jobs worldwide!
Machine Learning for Absolute Beginners
The “Machine Learning for Absolute Beginners” training program is designed for beginners looking to understand the theoretical side of machine learning and to enter the practical side of data science. The training is divided into multiple levels, and each level is covering a group of related topics for continuous step-by-step learning.
Level 2 - Python and Pandas
The second course, as part of the training program, aims to help you start your practical journey. You will learn the Python fundamentals and the amazing Pandas data science library, including:
Python syntax for developing data science projects
Using JupyterLab tool for Jupiter notebooks
Loading large datasets from files using Pandas
Perform data analysis and exploration
Perform data cleaning and transformation as a pre-processing step before moving into machine learning algorithms.
Each section has a summary exercise as well as a complete solution to practice new knowledge.
The Game just Started!
Enroll in the training program and start your journey to become a data scientist!