IBM Data Science with Python Basics
About Data Science
Data science provides meaningful information based on large amounts of complex data or big data. Data science combines different fields of work in statistics and computation to interpret data for decision-making purposes.
A data scientist collects, analyzes, and interprets large volumes of data, in many cases, to improve a company’s operations. Data science professionals develop statistical models that analyze data and detect patterns, trends, and relationships in data sets.
What is Python?
Python is an object-oriented programming language with integrated dynamic semantics, used primarily for application and web development. The widely used language offers dynamic binding and dynamic typing options.
Why Python for Data Science?
Python is one of the most popular languages in Data Science, which can be used to perform data analysis, data manipulation, and data visualization. Python offers access to a wide variety of data science libraries and it is the ideal language for implementing algorithms and the rapid development of applications.
The programming requirements of data science demand a very versatile yet flexible language which is simple to write the code but can handle highly complex mathematical processing. Python is most suited for such requirements as it has already established itself both as a language for general computing as well as scientific computing. Moreover, it is being continuously upgraded in the form of a new addition to its plethora of libraries aimed at different programming requirements. Below we will discuss such features of python which makes it the preferred language for data science.
- It is simple and easy to learn, we can achieve results in fewer lines of code.
- Its simplicity also makes it robust to handle complex scenarios with minimal code and much less confusion on the general flow of the program.
- It supports cross-platform, thus same code works with multiple environments.
- It executes faster than other similar languages used for data analysis like R and MATLAB.
- Its excellent memory management capability, especially garbage collection makes it versatile in gracefully managing a very large volume of data transformation.
- Python has got a very large collection of libraries and packages, which serve as special-purpose analysis tools where we can directly use code from other languages (Java or C).
About the course on IBM Data Science with python
This Python basics course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you’ll be ready to create your first Python scripts on your own.
Start your learning of Python for data science, as well as programming in general with this introduction to Python course. This beginner-friendly Python course will quickly take you from zero to programming in Python in a matter of hours and give you a taste of how to start working with data in Python.
After its completion, you will be able to write your own Python scripts and perform basic hands-on data analysis using our Jupyter-based lab environment. If you want to learn Python from scratch, this course is for you.
Also you can start creating your own data science projects and collaborating with other data scientists using IBM Watson Studio. When you sign up, you will receive free access to Watson Studio. Start now and take advantage of this platform and learn the basics of programming, machine learning, and data visualization with this introductory course.
The course on IBM data science with python basics consists of 5 weeks module as:
- Your first program
- Expressions and Variables
- String Operations
Python Data Structures
- Lists and Tuples
Python Programming Fundamentals
- Conditions and Branching
- Objects and Classes
Working with Data in Python
- Reading files with open
- Writing files with open
- Loading data with Pandas
- Working with and Saving data with Pandas
Working with Numpy Arrays
- Numpy 1d Arrays
- Numpy 2d Arrays
What you’ll learn
The objectives of this course is to get you started with Python as the programming language and give you a taste of how to start working with data in Python.
In this course on IBM data science with python basics, you will learn about:
- What Python is and why it is useful
- The application of Python to Data Science
- How to define variables in Python
- Sets and conditional statements in Python
- The purpose of having functions in Python
- How to operate on files to read and write data in Python
- How to use pandas, a must have package for anyone attempting data analysis in Python.
You should be familiar with basic Mathematics algorithms.
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Specification: Python Basics for Data Science