Four Mini-Projects for Python Beginners

3. Bootcamp

This will help you dive deeper in your Python programming knowledge. The framework that you’ll need here is the Django framework.

Bootcamp is basically a concept of an enterprise social network. It can be used to help developers or people belonging to one community collaborate and share experiences better. Its motive is to be closed and run inside a company only.

The whole idea will be to have a simple feed, just like Twitter. It will allow users to share links and post their thoughts and also keep track of everyone else in their community. It can also have a QnA section like StackOverflow where developers can post questions related to the business, software, or projects.

Here are a few things that you should definitely include as a part of your Bootcamp project:

– Feed App (A Twitter-like microblogging platform)

– Live feed updates

– Comments and likes

– Track comments and activities

– Articles App: 

this can be a collection of resource relevant to the users of the Bootcamp application. It can be a separate section other than the news feed which will contain all the necessary articles.

– QnA app (a StackOverflow-like platform)

– Messages

– Simple async messages

– Tracking of read/unread

– Search app: to help users search through their feed.

4.python mini projects Machine Learning Gladiator

Machine Learning Gladiator is one of the fastest ways to build practical intuition around ML.

The goal of this project will be to take the out-of-the-box models and apply them on different data sets. This project is completely amazing, especially for beginners, for three main reasons:

First, you’ll get to build intuition for model-to-problem fit. This will help you understand which models are robust to missing data? Which models handle categorical features nicely? Ofcourse you can read through the theory and find the answer, but it’s always better to learn by seeing things in action.

Second, the project will help you acquire the invaluable skill of prototyping models in real-time. When it comes to real-world problems, it’s often difficult to know which model will work best for you without trying it out.

Finally, this project helps you master the workflow of model building. You’ll get to practice:
– Importing data
– Cleaning data
– Splitting it into train/test or cross-validation sets
– Pre-processing
– Transformations
– Feature engineering

Because you’ll use out-of-the-box models, you’ll have the chance to focus on honing these critical steps.

For this project, you can use the following data sources:

UCI Machine Learning Repository – It contains a collection of more than 350 searchable datasets that cover almost every subject matter. You’ll surely find datasets that fit your need.
Kaggle Datasets – This contains more than 100 datasets uploaded byt he kaggle community. There are some really interesting datasets here, including PokemonGo spawn locations.

All of these projects are pretty basic, and can get you up and running in the world of Python programming. Further, if you find yourself stuck anywhere while trying to develop these games, do drop by at Coding Ninjas where there are courses around Python. These courses cover the concepts of Python with data structures, and are good enough to take you from ground zero to the top.