Coursera has introduced guided projects for students to experience more hands-on labs. Students who are studying data science or in the final year will find this helpful. We’ve chosen to list the 7 best Coursera Data Science Projects from the platform.
The Data Science projects for freshers is designed to help students gain more experience by doing the labs. Student’s who have just finished their Data Science course will find these projects helpful. The more projects you do, the more skillful you’ll become that will help you during the interview.
The Coursera guided project costs are $10 per project course. Every guided project comes with pre-configured desktops with all the necessary tools. All you’ve to do is follow the instructor’s guide and complete the project. You may also check out the list of all Data Science guided projects available in Coursera.
Why is it Important?
In today’s world, just having the Data Science certification won’t help you get a job. But, having worked on multiple projects will benefit you. Further, it also helps in creating a resume and building a Linkedin portfolio. For the best results, we recommend that you take more than a few projects.
Now let’s check out all the best data science projects for beginners offered by Coursera. You may also check out the best Coursera Machine Learning projects.
Best Coursera Data Science Projects for Beginners 2020
1. Build a Data Science Web App with Streamlit and Python
This Data Science project course will teach you to build your first web app using Python and Streamlit. If you already know how to write Python scripts using the Panda library, you’re good to take this project. Create dashboards by writing a Python code with less than 100 lines.
By the end of the project, you will be confident in using Python and Streamlit to build web apps. The web apps that you build here is interactive. All this can be achieved with no background of web development experience. So far, more than 8k students have enrolled in this Coursera Data Science Project.
2. Plots (Graphics) for Data Science
This Data Science project tutorial will teach you Data Visualization techniques in Data Science. It is a Data Science project with Python. The students will use the Python programming language for plots and Data Visualization. Students will learn the basics knowledge of data visualization.
You will develop the skills to create different types of charts and plots. By adding this Data Science project course to your resume will have many opportunities. The goal of the project is to create and visualize different types of charts and plots. This project will be helpful even for Machine Learning engineers as well.
3. Network Data Science with NetworkX and Python
These Coursera Data Science Projects are most suitable for freshers or beginners, which they can add to their online or offline portfolios. By working on more projects, you will continue to build your portfolio for a better Data Science career. With this project, you will perform visualization and network analysis on datasets.
With the datasets, you will generate several kinds of random graphs. You will begin by loading data into graphs and subgraphs. The course duration is 1 hour long. It comes with a pre-configured cloud desktop with split-screen video training.
4. Predict Ideal Diamonds over Good Diamonds using a Random Forest using R
This is Data Science projects using r. In this project, you will learn to complete a random training and test set from one Data Source using an R function. You also begin to practice creating a Factor/Binary Variable on a data set.
The project aims to get the desired result of predicting the ideal diamonds using a random forest using R. You can complete the project in an hour. Machine Learning and Data Analytics students can also take part in this project.
5. Create Interactive Dashboards with Streamlit and Python
This 2 hours long Data Science project will teach you to build your first interactive data dashboard. The dashboards are creating using both Python and Streamlit library. Here you will visualize, explore, load, and interact with data to generate the dashboards.
All the dashboards that you create here are done with less than 150 lines of Python code. By the end of the project course, you will be comfortable using Streamlit and Python to build web apps and dashboards. Over 3k students have enrolled in this Coursera data science project.
6. Perform Sentiment Analysis with scikit-learn
In this project course, you will learn the basics of sentiment analysis to build a logistic regression model. This logistic regression model is then used to classify movie reviews based on positive or negative reviews. The data used here is from the popular IMDB dataset.
The goal is to use a simple logistic regression estimator using Python’s scikit-learn. Here you’ll learn to clean and pre-process the text data, use NLTK to perform feature extraction, tune model hyperparameters, and evaluate model accuracy. As many as 5k students have taken this Data Science project.
7. Linear Regression with NumPy and Python
The Linear Regression with NumPy and Python is a Data Science project tutorial. Here you’ll learn how to implement the gradient descent algorithm from scratch. Using matplotlib, you will then create data visualizations and plots.
It also includes some of the popular Machine Learning libraries such as statsmodel and scikit-learn. The project follows the splits-screen video, where you follow the instructor’s step-by-step guidelines throughout the project.
This is the list of best Coursera Data Science projects for freshers in 2020. To become successful in the Data Science career, we recommend taking more than a few projects to have vast exposure in the field.