Developing Data Science Projects With Google Colab
- Development
- Apr 25, 2025

Developing Data Science Projects With Google Colab, available at Free, has an average rating of 3.4, with 9 lectures, 2 quizzes, based on 30 reviews, and has 2493 subscribers.
You will learn about How to use Google Colab through your internet browser How to design a data science project How to train and evaluate a machine learning model How to deploy a machine learning model in your application This course is ideal for individuals who are This course is for Intermediate data science and machine learning enthusiasts/learners. It is particularly useful for This course is for Intermediate data science and machine learning enthusiasts/learners.
Enroll now: Developing Data Science Projects With Google Colab
Summary
Title: Developing Data Science Projects With Google Colab
Price: Free
Average Rating: 3.4
Number of Lectures: 9
Number of Quizzes: 2
Number of Published Lectures: 9
Number of Published Quizzes: 2
Number of Curriculum Items: 11
Number of Published Curriculum Objects: 11
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
This project is for anyone who wants to develop Data science and Machine learning projects but having limited resources on his computer and limited time. In less than 2 hours, you will learn how to develop and deploy a fake news detection data science project!
In essence, you will learn,
– how to design a real life data science project
– how to get data to train a machine learning model
– how to clean and preprocess your data
– how to create and train a model to learn from your data
– how to evaluate the performance of the trained model
– and finally, how to deploy the model in any real-life application of your choice.
According to wikipedia,
“Google Colaboratory (also known as Colab) is a free Jupyter notebook environment that runs in the cloud and stores its notebooks on Google Drive. Colab was originally an internal Google project; an attempt was made to open source all the code and work more directly upstream, leading to the development of the “Open in Colab” Google Chrome extension, but this eventually ended, and Colab development continued internally. As of October 2019, the Colaboratory UI only allows for the creation of notebooks with Python 2 and Python 3 kernels; however, an existing notebook whose kernelspec is IR or Swift will also work, since both R and Swift are installed in the container. Julia language can also work on Colab (with e.g. Python and GPUs; Google’s tensor processing units also work with Julia on Colab.”
Course Curriculum
Chapter 1: Introduction
Lecture 1: Setting up Google Colaboratory for Data Science Project
Lecture 2: Project design approach and getting data
Lecture 3: Overview of the basic tools in Google Colaboratory
Lecture 4: Data visualization and data cleaning
Lecture 5: Data labelling and feature extraction
Lecture 6: Model creation and training
Lecture 7: Model evaluation
Lecture 8: Saving and downloading/exporting your model
Lecture 9: Model deployment
Instructors

Nawas Naziru Adam
Robotics and AI Engineer
Rating Distribution
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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