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Nowadays Data science has become one of the important technologies because of the continuing surge in data due to increased usage of the internet, social media, smartphone, etc.. Data science is used by industries, finance, education and businesses to extract information from huge chunks of data to plan strategies for their businesses.
If you are a beginner to data science and want to develop a career as a data scientist. The best way is to develop data science projects. Even though your resume is decorated with a variety of certifications, interviewers will look into your practical skills. Developing data science projects for final year academics will add more value to your resume.
This article focuses on data science project ideas for students willing to progress a career path as a data scientist. You can find data science projects in R, data science projects in python, data science projects using machine learning, etc.
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Before getting started, let us discuss some basics,
Data science is a combination of programming, machine learning, statistics, mathematics, and data analysis. With the help of all these, data science uses scientific methods and complex algorithms to extract information from large chunks of data.
Data scientists have transformed almost every industry by working with machine learning, Artificial Intelligence and make models that automatically self-improves by learning from mistakes. Below are some of the data science applications:
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Data science tools are used to avoid the usage of programming languages to execute data science techniques. These tools use user-friendly GUI, algorithms and predefined functions to make the task easy.
1. SAS - It is used by large companies to analyse data and specifically designed for statistical operations. SAS comes with numerous statistical libraries that help data scientists for organizing and modelling the data.
2. Apache Spark - It is a widely used data science tool and particularly used for stream processing and batch processing. Spark comes with a lot of Machine learning APIs that helps Data scientists to make powerful predictions with the given data.
3. BigML - It comes with a cloud-based GUI environment that you can use to process machine learning algorithms. BigML uses a broad variety of machine learning algorithms like classification, clustering, time-series forecasting, etc.
4. Excel - It is a powerful analytical tool for data science. As it comes with various tables, filters, formulae, slicers, etc. It is widely used for complex calculations, data processing and visualization.
5. Tableau - It is used for data visualization and comes with powerful graphics to make the visualization more interactive. Tableau has the ability to interface with spreadsheets, databases, OLAP cubes, etc.
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Check out the below list for more data analytics tools:
Programming languages are used to implement algorithms to extract useful data. It is suggested that data scientists should learn at least one programming language as it is essential to perform various data science functions. The following are the programming languages used for data science:
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Many beginners spend a lot of time learning theoretical concepts and forget to implement them practically. Always learning by doing projects will help you to understand the concepts properly. This part of the article gives you 10 interesting data science projects that you can develop and learn as a beginner:
1. Boston house prediction using machine learning: House price prediction models are used by real estate agents to get the valuation of houses. In this data science project, you will create a model to predict the house prices in the Boston area. While working on this project, you will learn about machine learning algorithms, evaluation and visualization of data.
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2. Movie recommendation system data science project: The aim of this project is to develop a model to recommend the movie watchlist for the user based on the historical data. Have you ever wondered how Netflix or Amazon prime keeps you on the loop by suggesting your favourite movies? As part of this data science project, you will develop a similar movie recommendation model using python language.
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3. Brain tumour detection using deep learning: This data science project is used in healthcare industries to analyse the brain images and predict tumour growth. You will use deep learning, a data science technique to detect the brain tumour. As part of this project, you will work with tools like TensorFlow and Keras.
4. Fraud detection using machine learning: In this data science project, you will use card transactions dataset to classify genuine and fraudulent credit card transactions. This data science project is used in banking sectors to reduce transaction frauds. You will learn concepts like SelectKBest features, Linear regression, Gaussian Naive Bayes algorithm, Confusion matrix, etc.
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5. Handwritten digit recognition: This data science project uses MNIST dataset of handwritten digits, a famous one among machine learning enthusiasts and data scientists. You will use Convolutional Neural Networks to recognize the handwritten digits.
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6. Customer segmentation: Many companies make use of this data science project to identify and segment customers to target the user base. You will use K-means clustering to group customers based on characteristics like interest, gender, age, and spending habits. Customer segmentation is the best example of unsupervised learning.
7. Breast cancer classification: Breast cancer is one of the common diseases among women. Early diagnosis of breast cancer will reduce the risk and increase the chance of survival. One more healthcare-related data science project in this project you will use Deep learning technique along with python programming language to detect breast cancer. Keras library is used for classification.
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8. Traffic sign recognition: Traffic rules are very important that everyone should follow to avoid accidents. With the advancement in self-driving cars, it is mandatory to train AI models to detect the Traffic signs. In this data science project, you will use the German Traffic Signs recognition benchmark dataset to develop a model to recognize the traffic sign.
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9. Sentiment analysis using twitter dataset: Sentiment analysis is used in fields like marketing, politics, etc to predict the public behaviour. In this data science project, you will use algorithms like Naive Bayes, Package Tidytext, Decision trees, etc.to identify and categorize the user’s attitude towards a particular product or topic.
10. Detecting Parkinson’s disease: In this data science project, you will develop a system to detect the symptoms of Parkinson’s disease in the human body. You will use UCI ML Parkinsons dataset to detect the neurodegenerative disorder.
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Also, check the below list for more interesting data science projects:
These are some real-time projects that will help you to boost your knowledge and skills in data science.
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