According to the TIOBE Index for January 2022,
Python is the programming language with the highest increase in ratings in one year,
making it officially the top choice of employers and professionals alike.
In fact, it has become a key prerequisite to landing a job in data science. Luckily,
Python is also very beginner friendly. So, if you’re an aspiring data analyst or data scientist,
learning Python is certainly the way to go. That said, our job is to make every step of your
learning curve easy and enjoyable. So, If you’re still new to Python, you might want to start
for free with our Introduction to Python course. We’ve provided a link in the description. But if
you already have some basic Python experience and want to take it to the next level, in this video
you’ll discover 4 interesting Python projects for beginners – all including code for practice!
Great! So, let’s start with project number 1 - Uber Trips Analysis
Since it was founded in 2009, Uber has become one of the most famous unicorn companies, offering its
services to more than 80 countries worldwide. This Python project for beginners aims to
analyze Uber rides to detect specific patterns, such as the busiest day or
the time with the lowest number of rides. And as you might expect, this is the easiest
project to start with. You will get familiar with the common steps of analyzing a dataset and how
to draw insights from data through visualizing the relationship between different variables.
In our opinion, there are 3 main reasons why this is an interesting Python project to try out.
First, it’s really easy and doesn’t take much time.
Second, since it’s famous, thousands of people have shared their code on GitHub and Kaggle,
so you have the chance to discover different ways to analyze the same dataset. And, finally,
despite its simplicity, this quick project is quite useful because it will help you solidify
the foundational rules of coding in Python. By doing this project you will learn how to:
o Read a dataset and display records from it o Use your detective’s hat and uncover hidden
patterns in data o Find the
relationship between different variables o Draw insights by visualizing these relationships
Python Project 2: The Discovery of Handwashing
Prior to the nineteenth century, hygiene was frowned upon. People simply didn’t understand
the risk of not washing their hands. This unreasonable behavior caused many deaths,
especially in hospitals where most doctors—unlike today—never washed their hands before surgeries.
In the mid-1800s, the Hungarian physician, Dr. Ignaz Semmelweis, decided to do something about
this tragedy. He started investigating the reasons behind the deaths in Vienna general hospital
and those of women giving birth in particular. After analyzing data from Clinic 1 and Clinic 2,
it turned out the proportion of deaths in Clinic 1 is much higher than that in Clinic
2. Then he was able to investigate further and find the cause through data analysis.
What’s truly exciting about this project compared to the other Python projects for beginners,
is that you will recreate the steps that someone did 200 years ago!
What Will You Learn from This Python Project?  Read a dataset and display records from it
 Display the relationship between variables through different periods
 Visualize the effect of handwashing on decreasing the number of deaths
The third Python Project we recommend - Predicting Parkinson’s Disease with XGBoost
Can you improve people’s health and save their lives with just a few lines of code?
The answer is yes. Data science has countless
applications in healthcare, and one of them is to predict certain diseases, especially chronic ones.
Consider this. If you’re planning to go out, you normally check the weather news the day before
so that you can prepare. if it’s going to rain, you’ll grab an umbrella and wear a raincoat.
And if the forecast says it is going to be hot, you’ll wear light clothes. The same approach
is valid for disease prevention. If you are aware of the risk to catch a certain disease,
you will have the time to think and prepare, which can save a lot of suffering and money.
In this project, you’ll carefully analyze a dataset of 195 records to predict the
likelihood of having Parkinson’s disease using an XGBBoost model.
What Will You Learn from This Python Project?
 How to Read and explore data  Understand the relationship between
different variables through visualization  Carry out feature selection to determine
the variables that are most related to the target output.
 Build a machine learning model  Use metrics, such as accuracy and ROC curve,
to evaluate the model’s performance.  Save the trained model into a file
to be used for future predictions. Python Project 4: Detecting Fake News
You see them every day. News is an integral part of our perception of the world,
so it’s really important to pay attention to genuine media reports and ignore the
untrustworthy ones. How can you possibly do this? Again, the answer is by using data science.
In this project, you’ll apply a PassiveAggressiveClassifier to
differentiate between real and fake news. The exciting thing about this beginner
Python project is that you can turn it into a live product that helps people!
This Python project will teach you how to:  Read and explore a textual dataset
 Build a machine learning model
with TfidfVectorizer  Create a confusion matrix
and understand its components  Evaluate the model’s accuracy
The links we’ve provided in the description of the video would allow you to access these projects
and give them a try. If you want to learn more on topics like data strategy, data visualization,
machine learning, and business analytics the 365 data science platform might be the perfect
fit for you! So, make sure you check out the special offer we’ve provided in description.