Recent reports suggest that people are taking numerous data science and AI courses to stay abreast of the latest technologies. However, organisations are still witnessing a shortage of skilled applicants as these courses aren’t making applicants do varied projects. Besides, e-courses are often easier, allowing people to complete the course and get certificates. No doubt these courses are helpful in getting started with data science, however, aspirants need to implement those learnings by doing diverse projects for improving their expertise.
300 applications for ML internship. Not a single one can write a scikit pipeline and normalise input data.
— Sandeep Srinivasa (@sandeepssrin) December 23, 2019
Everyone has advanced ML and data science degrees from all kinds of cool programs. And everyone has worked on CNN.
And everyone has published papers.
In this cut-throat competition, it is extremely necessary for aspirants to stand out of the crowd. Consequently, they should focus on adding multi-dimensional projects that will add value to the portfolio. This will enable applicants to demonstrate their capabilities of implementing data science skills in numerous challenges.
Polish The Information
Data is still widely unstructured, and developers have no other alternative for getting high-quality data. Therefore, it is of paramount importance that aspirants work on projects that require extensive cleaning of data. Instead of obtaining the test and train datasets from various platforms, one should collect messy and untidy data for their projects. This will help aspirants to showcase their expertise in data wrangling.
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Check these data wrangling course and dataset sources for learning and getting your hands dirty to master the skill.
Interactive Data Visualisation
Data visualisation is a crucial aspect for organisations as it provides a lot of insights into data. Often, developers are expected to explain their findings through reports to non-experts. This is where one needs to provide interactive data visualisation for allowing anyone to assimilates the findings, through interactive plots.
This not only helps people with minimal data science skills but also to other data scientists to quickly understand the data and findings. Consequently, aspirants should be expert in making effective visualisations using both algorithms and business intelligence tools.
Learn from this PowerBI resources and get the datasets from these sites to explore through visualisation.
Sentiment Analysis
With a plethora of text being generated every day right from internal documents to news reporting to even social media post. Understanding people’s emotions have become vital for firms to build products and services around them. Firms nowadays prefer to analyse what their customers are writing on their social media and other feedback in text format for getting accurate insights into customers perspective about their products.
The ability to extract insights from the text will assist aspirants in analysing and determining people’ emotional tone by doing projects related to text analysis.
Follow the link to get an understanding of sentiment analysis projects.
Customer Segmentation & Recommendation
Differentiating between customers for organisations is paramount to provide bespoke solutions through recommendation. In Particular, firms with numerous products, they find it difficult to provide superior customer experience. Therefore, they seek data scientists, who can help them in understanding their customers to deliver effective solutions. Customers’ requirements are diverse and often vary frequently, so continuously monitoring to unveil the requirements is crucial for firms.
Especially in retail and over-the-top streaming service providers distinguishing users and then recommending the product they would like, based on their historical behaviour is essential for driving business growth. Consequently, projects related to clustering and recommending will assist aspirants in showcasing their expertise in solving real-world business challenges.
Check this music recommendation project for getting familiar with segmentation and recommendation.
Fraud Detection
Frauds are common for firms as people often try to cheat and get benefits by exploiting technical faults. Such practices are prominent in the healthcare, retail, and finance sector. While user in healthcare makes fake insurance claims, in finance, they try to steal money through unauthorised transactions. Detecting frauds before it significantly affects organisations is crucial for their business growth, thus aspirants should have projects related to fraud detection.
Here’s a credit card fraud detection that will help you in getting started with fraud-related projects.
Supply Chain
A robust supply chain not only helps in streamlining the delivery of products but also reduces operational costs. Optimising supply chain has been proven beneficial for organisations and customers alike. Therefore, companies desire to analyse and improve their supply chain by streamlining the workflow. Thus, aspirants who have supply chain projects differentiate themselves from the rest, resulting in getting a better job offer.
Learn supply chain analytics from here and apply it with these datasets.