2 mins to read This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Upon its completion, you’ll be able to write your own Python scripts. If you want to learn Python from scratch, this course is for you.
This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours.
Upon its completion, you’ll 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.
COURSE SYLLABUS
Module 1 – Python Basics
- Your first program
- Types
- Expressions and Variables
- String Operations
Module 2 – Python Data Structures
- Lists and Tuples
- Sets
- Dictionaries
Module 3 – Python Programming Fundamentals
- Conditions and Branching
- Loops
- Functions
- Objects and Classes
Module 4 – Working with Data in Python
- Reading files with open
- Writing files with open
- Loading data with Pandas
- Working with and Saving data with Pandas
Module 5 – Working with Numpy Arrays and Simple APIs
- Numpy 1D Arrays
- Numpy 2D Arrays
- Simple APIs
- API Setup
- This course is self-paced.
- It can be taken at any time.
- It can be audited as many times as you wish.
- There is only ONE chance to pass the course, but multiple attempts per question
- Basic Math
How to Enroll:
- Choose your desired certificate program on the IBM website.
- Create an Amazon if you don’t have one.
- Select specific courses within your chosen program.
- Enroll in courses, and pay if necessary.
- Access course materials and complete requirements.
- Prepare for and take certification exams if required.
- Earn your certificate upon successful completion.
- Be aware of maintenance or renewal requirements, if applicable.
