In this post you will know some the best projects i can do to learn Machine learning and data Science.The best way to build trust with a hiring manager is to prove you can do the work that they need you to do. With data science, this comes down to building a portfolio of projects. The more interactive the projects are, the more the companies will trust that you'll be an asset to the business. And the greater are your chances of getting hired.

Considering the current industry trends, the best way to showcase your Data Science skills are these 4 kinds of projects:

Data Cleaning

Data Analysis

Interactive Data Visualizations

Machine Learning

Here are a few popular projects based on these above skills that you could include in your future portfolio—

Projects based on Data Cleaning: Data scientists approximately spend up to 80% of their working time on cleaning data. So, if you can show that you’re experienced at cleaning data, you’ll eventually be more valuable. To create a Data cleaning project, you first need to pick a messy dataset and start cleaning it by removing distortions or missing data points. You can try these datasets to begin with-

Ticket Sales Data- In this you will strengthen your skills by importing and cleaning some messy online ticket sales data. This includes removing redundant information, deleting duplicates, identifying event dates and sorting them etc.

World Food Facts- The data will include some popular food items worldwide with their nutritional values and place of origin. Your goal is to eliminate useless information, remove and sort pairs of items holding duplicate values and replacing missing values.

Data Analysis Projects: This involves drawing conclusions and generating questions that lead to interesting discoveries. Here are a few popular projects you should consider-

Movie Recommendation System- Recommender systems are considered valuable even for large companies like Google or Facebook. As it is important from a perspective of revenue and engagement. So no doubt in going for this project. Beginners are able to practice their analytical skills and can build a model of their personal movie recommendation system.

Diabetes Prediction- Make analyses based on the patient’s characteristic data set to predict whether he is diabetic or not. Your goal is to build a project to analyze datasets containing attributes like glucose level, blood pressure, age, etc.

Projects based on Visualisation: Data Visualisation requires you to have a real hang of some popular tools like Tableau, Plotly, Qlikview etc. Using these tools, you have to create some interactive visualizations for a better understanding of the analysis. You can consider these projects, to begin with-

Designing a business plan for insurance distribution- In this, you would be forecasting the business for the upcoming years by exploring the hidden trends, extrapolation, assumption and finally summarizing the solutions through visualization.

Real Estate price prediction- Make predictions using Real Estate market data containing values like crime rate, age, accessibility, population, etc. Built an interactive visualization for an effective stock price.

Machine Learning projects: A machine learning project is another important piece of your data science portfolio. Now you should not approach towards every algorithm, but rather pick some basic and widely used ones like Logistic Regression, K-means clustering, Naive Bayes etc.

Twitter Stream Project- A lot of companies monitors mentions from their customers on Twitter to react to the negative ones quickly. For example giants like Uber and Airtel respond to negative tweets fast and find out what the problem is and how they can solve it. You can make this project using a convenient Twitter API and sentiment analysis algorithms to detect such tweets in the whole stream.

Spam or Ham- One of the classic data science problems is a spam detection. You can build a model for detecting spam emails and messages. Additionally, you can also add spamming user comments to hide them in the browser. This will showcase your statistical skills and some classic machine learning.

All these are some out of the box projects which can show your skills as a complete Data Scientist. Having worked on these projects will provide you an edge over the peers. Also listing these in your data scientist resume can improve your chances of landing a high-paying job. You can easily get the data sets for these projects online or at Kaggle. Also you should try to work on end to end data science projects available on public domains like Datacamp, MNIST, Github etc.

Although all these are some unconventional and easy to build projects, you should mainly focus on projects based on Data Cleaning and Analysis. Since these are the primary skills that companies usually look for before hiring freshers for data science roles.

Also you can try Edwisor,which is a popular platform for working on some modern data science projects. Here you can get a curated career path for data science in which you can learn all the tools as well as work on many industry level projects. Alongside this, a lot of top companies like American Express, Data Peace, Paisa Bazaar and many startups hire data scientists from here on the basis of the projects they do. So get some great job opportunities too. So give it a try!