Advance Your Data Science Career with edX's Certification in Python Basics

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Advance Your Data Science Career with edX's Certification in Python Basics

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Pokala Venkata Narayana

07 June 2023

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Advance Your Data Science Career with edX's Certification in Python Basics

Course Overview

Python Basics for Data Science course by edX gives you an introduction to working with data in Python. It is easy to follow and will enable you to learn programming in Python within a few hours. After the course is completed, you will be able to write Python scripts and do basic data analysis in our Jupyter-based laboratory environment. This course is designed for those who want to learn Python completely from scratch.

You can start the course anytime and you can take as long as you need to complete it. The portion you have covered in the course will be noted and your labs will be saved. However, it is strongly recommended that you do not take prolonged breaks between lessons as the mind tends to forget what it does not practice. There is only a single chance to pass the course, but you can take multiple attempts per question.

One of my instructors for this course, Joseph Santarcangelo is currently working as a Data Scientist at IBM. Joseph has a doctorate in Electrical Engineering. His research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition.

"This course has given me a good foundation in Python and added more strength in my resume."

- Pokala Venkata Narayana

Course Structure

The certification program is an intermediate-level self-paced course. It is spread over a duration of 5 weeks and requires learners to put in 5 hours per week. Some of the critical areas you cover in this curriculum include Python programming, Data Visualization, Exploratory Data Analysis, and more.

The professors associated with this course have degrees from renowned institutions in the field of cloud development. The course thus offers a great opportunity to study under international professors. The applicants get to be a part of a Capstone project that enhances their understanding of concepts and lets them learn in an innovative way.

The course offers instructor-moderated discussions that are great opportunities to make and build connections. The learners get to enjoy the benefits of hands-on training. The curriculum prepares the learners for a career in the real world. Moreover, the prescribed modules of this course are detail-oriented, comprehensive and practical.

Technically, the course is spread over 5 prime modules:

  • Module 1: Python Basics
  • Module 2: Python Data Structures
  • Module 3: Python Programming Fundamentals
  • Module 4: Working with Data in Python
  • Module 5: Working with Numpy Arrays

Insider Tips

In order to get the best out of this course, I have included some important tips below that I think you might find useful.

Assessments or Grading Criteria:

This course contains many assignments and projects that will help you apply your skills and have hands-on experience. I recommend giving enough time and energy to these projects. You will get to learn something new from each project though it may be challenging at times.

The assessment method requires completing assignments and undertaking projects under various modules throughout the degree. These can be research-based or concept specific. The evaluations are designed to ensure continuous student engagement with the program and to encourage learning.

Technical Exhibitionism from the Course

  • 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.

Final Take

Currently, I am working as an Associate Engineer in Primesoft Solutions Inc. This course has given me a good foundation in Python and added more strength in my resume. In my current job, I am using the data science basics like string operations, functions ,oops concepts, loops and data structure.

Key Takeaways

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Work in a Jupyter-based laboratory environment.

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Free access to use IBM Watson Studio to create your own data science projects or collaborate with data scientists.

Course Instructors

Pokala Venkata Narayana

Associate Engineer

Currently working as an associate engineer.