Data Science Projects for Beginners

Your skill in anything increases exponentially when you work on projects, the same goes for data science.

Data Science, or for that matter concept or technology in the space of Analytics, is best learned via projects and practical implementation rather than going in-depth in theories & frameworks.

While it is important to understand a few of the theoretical concepts, and modeling techniques to kickstart an aspiring career in the field of data science; live implementation of these techniques on real-world data sets and finding relevant insights from those datasets & structures has no alternatives.

In order to enable students to test & evaluate their knowledge of data science & statistics in solving real-world problems; there are multiple global datasets that are present over the web for students to access free of cost. The subsequent two-section would deliberate on the available datasets; and possible projects which beginners can progress with on these datasets.

Here are the best beginner data science projects for you!

Global datasets available for students to work on

There are multiple datasets available on the web corresponding to different business problems which students can make use of. While a few of these datasets correspond to business problems for a more advanced audience, others can be used by beginners and intermediate users as well.

These datasets would make for very interesting data science mini-projects, depending on how creative you can get with them. A few examples of these datasets are mentioned below for reference –

1. Iris Dataset

This is the perfect dataset for beginners who plan to build a career in data science. Students focusing on pattern recognition or classification algorithms can surely refer to this dataset.

2. Loan prediction Dataset

This dataset related to the insurance sector contains 13 different variables which banks & insurance companies generally refer to before approving a loan for a customer.

3. Sales dataset of Bigmart

As the name suggests, this dataset transaction data focused on managing the sales of a business. The entire data set includes 12 variables all of which are directly or indirectly related to sales.

4. Time-series datasets

Data science is not all about studying and analyzing cross-sectional datasets; as it only describes an event at a particular period of time. Time series datasets have trended on various metrics such as weather, sales, traffic, and so on.

There are multiple other datasets as well which can be leveraged by students, but the above-mentioned are specifically catered to beginners. You can work on a beginner data science project with these datasets. The more projects you do, the more practice you'll get while building your portfolio!

Data Science projects for beginners

The above datasets (amongst others) can be used by students & beginners to solve a multitude of business problems – a few of the frequently preferred ones are mentioned below for reference –

1. Classification problems

Classification problems are an important building block of data science & machine learning which attempts to classify future observations into a particular category; based on the learnings from a training set. The Iris data explained in the previous section can be leveraged in this case.

2. Sales forecasting/prediction

Forecasting problems are key to solving business decisions as these are important considerations for devising a business strategy. The sales data mart can be used to solve such problems.

3. Logistic model on loan approval

The loan prediction dataset can be leveraged in this case to factor in different factors & variables to predict the risk score for any loan-seeking customer, and thereby prescribe whether the loan should be approved or not.