Data Science con Python - Elaborare e Visualizzare Dati
Learn data analysis & visualization with Python! Master NumPy, Pandas, Matplotlib, Seaborn & Plotly. Hands-on exercises & code included.
Course Content
Data Science con Python - Elaborare e Visualizzare Dati is an all-levels Udemy course taught by Michael Saccol. It runs 2h 54m, is taught in Italian, and includes a certificate of completion. Learners rate it 3.2 out of 5 from 3 reviews, with 16 students enrolled. It is a paid course, last updated January 2023.
Unlock the Power of Data: Mastering Data Processing & Visualization with Python
This course equips you with essential skills for a career in data science, focusing on the core processes of data processing and compelling data visualization. We'll leverage Python, one of the most popular and powerful programming languages for data analysis, building a strong foundation in its fundamentals.
Python Fundamentals:
- Variables: Learn how to store and manage data effectively.
- Input & Output: Master techniques for reading data from various sources and presenting results.
- Data Types: Understand different data types (integers, floats, strings, booleans) and how to work with them.
- Operators: Become proficient with mathematical, comparison, and logical operators.
- Control Flow: Utilize conditional statements (if/else) and loops for efficient data manipulation.
- Complex Data Structures: Explore lists, dictionaries, tuples, and sets for organizing and accessing data.
Data Processing with NumPy & Pandas:
- NumPy: Discover the NumPy library and its role in numerical computing.
- Arrays: Learn to create, manipulate, and perform operations on NumPy arrays.
- Indexing & Slicing: Master array indexing and slicing techniques for data extraction.
- Array Operations: Perform mathematical operations, statistical calculations, and more on arrays.
- Matrices: Work with matrices and linear algebra operations.
- Random Number Generation: Generate random numbers for simulations and data augmentation.
- Pandas: Uncover the Pandas library for data analysis and manipulation.
- Series & DataFrames: Understand and utilize Pandas Series and DataFrames for structured data handling.
- DataFrames Operations: Perform data cleaning, transformation, and analysis on DataFrames.
- Input/Output: Read and write data from various file formats (CSV, Excel, etc.).
- Handling Missing Data: Learn strategies for dealing with missing values in your datasets.
Data Visualization with Matplotlib, Seaborn & Plotly:
- Matplotlib: Explore the fundamentals of data visualization with Matplotlib.
- Basic Plots: Create line plots, scatter plots, bar charts, histograms, and more.
- Plot Customization: Learn to customize plots with titles, labels, colors, and annotations.
- Advanced DataFrames & Export: Visualize data directly from DataFrames and export plots in various formats.
- Seaborn: Enhance your visualizations with Seaborn, a library built on Matplotlib.
- Distribution Plots: Create histograms, kernel density plots, and other distribution visualizations.
- Categorical Plots: Generate bar charts, box plots, and other visualizations for categorical data.
- Regression Plots: Visualize relationships between variables using regression plots.
- Plotly: Create interactive and dynamic visualizations with Plotly.
- Scatter Plots, Line Plots, Bar Charts, Histograms: Build a wide range of interactive charts.
- Other Plot Types: Explore pie charts, 3D plots, and more.
Course Resources:
- Practice Exercises: Reinforce your learning with hands-on exercises.
- Exercise Solutions: Access detailed solutions to all exercises.
- Code Files: Download all code examples used in the lessons.
Want AI in your product? Hire the team behind TutorialSearch.io
LLM features, RAG, agents and automation wired into a real product — built by the devs who shipped this site.