Udemy – Learn Data Science Skills: Python, Pandas, Machine Learning 2024-6

Udemy – Learn Data Science Skills: Python, Pandas, Machine Learning 2024-6 Downloadly IRSpace

Apr 18, 2025 - 05:26 Updated: Aug 17, 2025 - 16:01

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Udemy – Learn Data Science Skills: Python, Pandas, Machine Learning 2024-6

Learn Data Science Skills: Python Pandas Machine Learning course. This course will introduce you to the skills necessary to become a competent data scientist. In today’s data-driven world, the ability to use and interpret data is not only a valuable skill, but a critical advantage. Whether you’re an aspiring data scientist, a seasoned professional looking to expand your skills, or an entrepreneur aiming to use data to make strategic decisions, our comprehensive data science course offers a transformative learning experience. The course begins with a fundamental review of data science and introduces you to its principles and importance in various industries. You will explore the differences between data science, data engineering, and data analytics and gain a clear understanding of the roles and applications of each. Through real-life case studies and examples, you’ll see how data science is driving innovation and influencing decision-making processes across sectors.

To equip you with the tools you need to effectively analyze data, the course covers essential programming languages such as Python and R. Whether you’re manipulating data with Pandas, performing numerical operations with NumPy, or creating insightful visualizations with Matplotlib and Seaborn, you’ll develop a diverse skill set that forms the backbone of data science projects. During the course, you will apply your new knowledge in practical projects that simulate real-world challenges. Whether it’s forecasting house prices using regression models or building a web application for interactive data analysis, these projects provide a platform to showcase your skills and build a professional portfolio.

What you will learn in the Learn Data Science Skills: Python Pandas Machine Learning course

Understanding the fundamental concepts of data science
Understanding the applications and impact of data science on industry
Using essential data science libraries such as Pandas, NumPy, Matplotlib and Seaborn
Installing Python and setting up the development environment on Windows and macOS
Understanding the concept of virtual environments and creating/managing them
Getting to know Jupyter Notebook and using it for interactive data analysis
Explore and manipulate data using Pandas DataFrames
Create and manipulate Pandas Series for efficient data management
Load the dataset into Pandas and perform initial data inspection and cleaning
Data transformation and analysis using Pandas methods
Data visualization using Matplotlib and Seaborn for insights and reporting
Understand supervised, unsupervised and reinforcement learning techniques
Data preprocessing for machine learning models, including handling missing values and encoding categorical variables
Building, training and evaluating machine learning models using scikit-learn
Measure model performance using metrics such as accuracy, confusion matrix, and classification report
Deploying a machine learning model for real-time predictions and understanding model interpretation techniques

This course is suitable for people who

Future data scientists
Students and graduates
Professionals changing career paths
Data analysts and engineers
Entrepreneurs and business owners
Anyone interested in data science

Details of the Learn Data Science Skills: Python Pandas Machine Learning course

Publisher: Udemy
Instructor: Skill Tree
Training level: beginner to advanced
Training duration: 7 hours and 13 minutes
Number of courses: 109

Course headings

Learn Data Science Skills: Python Pandas Machine Learning course prerequisites

Basic Computer Literacy
Basic knowledge of algebra, including variables, equations, and basic operations.
No prior programming experience required, but familiarity with the basics of programming concepts (e.g., variables, loops, conditional statements) is beneficial.
Access to a computer with internet connectivity.
Ability to install software, including Python and necessary libraries (installation instructions will be provided)