Udemy – Data Science Tools: Python, Pandas, Machine Learning, EDA 2024-6

Data Science Tools course: Python, Pandas, Machine Learning, EDA. Our course begins by exploring the basics 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 role and applications of each. Through real-world case studies and practical examples, you’ll see how data science is driving innovation and influencing decision-making processes across sectors. Sign up today and begin a journey to data science mastery – a journey with a new discovery every time.

What you will learn in the Data Science Tools course: Python, Pandas, Machine Learning, EDA

• Using essential data science libraries such as Pandas, NumPy, Matplotlib and Seaborn
• Distinguish between structured and unstructured data
• Gaining skills in Python programming language for data analysis
• Understanding the fundamental concepts of data science
• Distinguish between data science, data engineering and data analysis
• Understanding the applications and impact of data science in industry
• Installing Python and setting up the development environment on Windows and macOS
• Getting to know Jupyter Notebook and using it for interactive data analysis
• Explore and manipulate data using Pandas DataFrames
• Creating and manipulating Pandas Series for efficient data management
• Upload datasets to 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
• Using statistical techniques for data exploration and hypothesis testing
• Definition of machine learning and its application in data science
• Understand supervised, unsupervised and reinforcement learning techniques
• Data preprocessing for machine learning models, including handling of missing values ​​and coding of 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

• Data analyst and data engineer
• Future data scientists
• Students and graduates
• Professionals who want to change their career path
• Entrepreneurs and business owners
• Anyone interested in data science

Data Science Tools course specifications: Python, Pandas, Machine Learning, EDA

• Publisher:  Udemy
• Instructor:  Bluelime Learning Solutions
• Training level: beginner to advanced
• Training duration: 8 hours and 49 minutes
• Number of courses: 122

Course topics on 7/2024

Data Science Tools course prerequisites: Python, Pandas, Machine Learning, EDA

• Basic Computer Literacy
• No prior programming experience required, but familiarity with the basics of programming concepts (eg, 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).
• Willingness to learn and explore new tools and technologies (eg, Jupyter Notebook).

Course images

Sample video of the course

download link

Download part 1 – 1 GB

Download part 2 – 573 MB

File(s) password: www.downloadly.ir

Size

1.5 GB