[UDM] Data Science Tools: Python, Pandas, Machine Learning, EDA Course (Jul 2024) + Resources

Course Introduction
The Data Science Tools: Python, Pandas, Machine Learning, EDA Course will provide you with a superb introduction to data science with Python and cover all of the essential skills that can be put into practice across sectors involving finance, healthcare, and marketing. You will get to know what data science deals with, how it contrasts with other areas, including analytics and engineering, and why it is one of the most sought-after skills of the day. The training is practical and project-based; hence, you learn by practice rather than theory.

Python & Pandas Basics
You will get started with installing your development environment to use Jupyter Notebook and virtual environments so that you can use your Python skills on real projects, whether you are using Windows or macOS. Next, you’ll learn about data preparation with Pandas and NumPy, the most common ways of preparing data familiar to most users: importing, cleaning up, joining, and transforming data in CSVs, Excel files, SQL tables, and elsewhere. In all this, you will get the chance to deal with missing values, data types, and make some conversions and ne,w valuable features.

Exploring & Visualizing Data
Another key aspect of the Data Science Tools: Python, Pandas, Machine Learning, EDA Course is exploratory data analysis (EDA), as you will learn how to explore and analyze data and derive conclusions. With Pandas, you will sort, filter, and aggregate data, and visualizing tools, such as Matplotlib and Seaborn, will make your discovery come to life with the help of charts, plots, and graphs. You will apply these skills in a case study where you will work on data-driven decisions and storytelling with data about customer churn in a streaming company.

Preparing for Machine Learning
Once you have mastered data cleaning and EDA, you will transition to preparing data for the machine learning models. You will be taught how to combine datasets and create features that are engineered and pass them to algorithms with scikit-learn. The Data Science Tools: Python, Pandas, Machine Learning, EDA Course will take forward the learning approach to supervised and unsupervised learning, in addition to the evaluation measures such as accuracy and confusion matrices. In the process, you will be provided with all the skills necessary to handle the whole data science process- obtaining raw data, creating predictive models, and more.