Description
Description
An increasing number of enterprises are embracing data science as a pivotal driver for informed business strategies. Irrespective of the industry, the capacity to glean insights from data holds paramount importance in maintaining competitiveness in today’s market. Python®, emerging as a frontrunner in data science, stands out with its extensive libraries, empowering data scientists to effortlessly load, analyze, manipulate, cleanse, and visualize data in user-friendly yet robust ways. This course is tailored to equip you with the essential skills to proficiently harness these pivotal libraries, enabling you to derive actionable insights from data, thereby delivering substantial value to the business.
Training Objectives
- Set up a Python data science environment.
- Manage and analyze data with NumPy arrays.
- Manipulate and modify data with NumPy arrays.
- Manage and analyze data with pandas DataFrames.
- Manipulate
- modify
- and visualize data with pandas DataFrames.
- Visualize data with Matplotlib and Seaborn.
Course Outline
- Lesson 1: Setting Up a Python Data Science Environment<br />
- Topic A: Select Python Data Science Tools<
- Topic B: Install Python Using Anaconda<
- Topic C: Set Up an Environment Using Jupyter Notebook<
- Lesson 2: Managing and Analyzing Data with NumPy<br />
- Topic A: Create NumPy Arrays<
- Topic B: Load and Save NumPy Data<
- Topic C: Analyze Data in NumPy Arrays<
- Lesson 3: Transforming Data with NumPy<br />
- Topic A: Manipulate Data in NumPy Arrays<
- Topic B: Modify Data in NumPy Arrays<
- Lesson 4: Managing and Analyzing Data with pandas<br />
- Topic A: Create Series and DataFrames<
- Topic B: Load and Save pandas Data<
- Topic C: Analyze Data in DataFrames<
- Topic D: Slice and Filter Data in DataFrames<
- Lesson 5: Transforming and Visualizing Data with pandas<br />
- Topic A: Manipulate Data in DataFrames<
- Topic B: Modify Data in DataFrames<
- Topic C: Plot DataFrame Data<
- Lesson 6: Visualizing Data with Matplotlib and Seaborn<br />
- Topic A: Create and Save Simple Line Plots<
- Topic B: Create Subplots<
- Topic C: Create Common Types of Plots<
- Topic D: Format Plots<
- Topic E: Streamline Plotting with Seaborn<
- Appendix A: Scraping Web Data Using Beautiful Soup
