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Python for Data Science Beginner
Learn the essential skills to write Python codePreview the first lesson free — get full access to all 24 lessons.
Beginner Provider : Nizar Dajani 6 chapters · 24 Lessons · 3h 2m in Arabic, German, English, Spanish, French, Portuguese, Chinese
Course Description
Python has grown into a very popular programming language, especially for data science. Its simplicity in coding and easy-to-use concepts make it the go-to language for programmers, as well as non-programmers like data scientists. During the early years, Python was primarily used for system scripting and small-scale projects. However, it quickly gained popularity among developers due to its simplicity, readability, and versatility. In the late 1990s and early 2000s, Python was used for a wide range of applications, including scientific computing, web development, and game development.
In this Python for Data Science course, you will discover the fundamentals of Python, and the basic programming skills needed to use it for data science. These fundamental skills will allow you to work with datasets of any size. You will be writing code in no time and enjoying the many features and tools that come with the Python installation.
What You'll Learn
- Recognize the different features of Python and why it became a popular programming language
- Explain how to use data in Python through variables, data types, operators, conditionals, loops, and functions
- Apply core Python data structures including lists, dictionaries, tuples, and classes and objects
- Identify and use Python libraries such as NumPy and Pandas for data science work
- Set up the Python environment by downloading and installing tools like IDLE, PyCharm, Anaconda, and Jupyter
- Work with strings, the Math module, requests, files, and command line processes and variables
Key Takeaways
- Python is a popular programming language for data science because of its simplicity, readability, and versatility.
- The course teaches the fundamentals of Python and the basic programming skills needed to use it for data science.
- These fundamental skills allow you to work with datasets of any size.
- The course covers Python libraries including NumPy and Pandas for data science tasks.
- Learners install Python and explore the features and tools that come with the Python installation, such as IDLE, PyCharm, Anaconda, and Jupyter.
Frequently Asked Questions
Who is this course for?
This Python for Data Science beginner course is suited to programmers as well as non-programmers like data scientists who want to learn the fundamentals of Python and the basic programming skills needed to use it for data science.
What will I learn in this course?
You will discover the fundamentals of Python, recognize its different features, learn how to use data in Python, and identify the different libraries to use with Python, including NumPy and Pandas.
Do I need prior programming experience?
No. This is a beginner course covering the fundamentals of Python, and it is described as suitable for non-programmers like data scientists as well as programmers.
What topics and tools does the course cover?
The course covers Python's history and popularity, downloading and installing Python, tools such as IDLE, PyCharm, Anaconda, and Jupyter, variables, data types, string methods, operators, conditionals, loops, functions, lists, dictionaries, tuples, classes and objects, requests, the Math module, NumPy, Pandas, command line processes, and files.
What skills will I gain from this course?
You will gain skills in Data Literacy, Data Manipulation Language, Data Science, Pandas, Python, and Scikit-Learn.
