Introduction
The world is ruled by massive infrastructures around the concepts of Big Data Management, IT Automation, Storage and Compute, and Artificial Intelligence. For a large part of the 21 st century, large enterprises focused only on growing their Big Data storage capabilities. But, today, the industry is heading toward automating the way these enterprises analyze Big Data and create real-time actionable opportunities or insights for businesses. The future of data management is – Data Science, an inter-disciplinary specialization that involves scientific study and analysis of different types of data, process, algorithms, and the software that manage these operations.
According to leading market research companies, data science market is yet to hit its “boom”, growing at 12% YoY in revenue and sales. By 2027, the demand for data science projects in India alone would take a lion’s share of revenue and sales — a whopping $100 billion. So, today, it’s very important to truly understand what data science is, and how mastering this field can add immense value to your career aspirations.
This article provides a quick snapshot of the data science career planning roadmap, and the various projects that will help you conquer the rather complex landscape, technology-wise.
Table of Contents
- Where to start with a data science project?
- Data science project (explained)
- Why choose open-source data sets?
- Data science projects for freshers tips
- Data science projects for resumes
- Resource to find more topics
- Conclusion
Let’s begin…
Where To Start With Data Science Project?
Starting with your right foot is the key to begin your first data science project for freshers . Data science professionals and analysts are constantly looking for new innovative ways to build data engineering projects to keep their necks ahead in the race. Starting with a simple “whack a mole” project is the best option.
You can simply pick any real-world problem to solve and start scratching the surface with the aim, shoot, and analyze methodology.
Most trainers recommend starting with a data mining project that involves significant workaround with Python programming, data visualization, and analytics.
If your objective is to start with a simple data science project as a fresher, you could explore brainstorming with problems facing the current finance and banking, automotive, social media monitoring (Twitter and Facebook), mobile application performance, e-commerce experience, telecom networking, and healthcare.
The closest you are to a digitally enabled and transformation industry, the easier it is for you to initiate a data science project in India . For example, Amazon’s Prime Day sale, or Flipkart’s Billion Dollar Sale, where you could work with millions of products sold at discount, and the volume of customers or shoppers keep waning and waxing as the sale timeline draws to an end.
By forecasting the results of these e-commerce sales volumes, you can help small-scale advertisers and Amazon product owners map their retail marketing tactics with better precision.
For example, your data science project could enable an e-commerce store to improve their inventory quality or increase their stock volume, or simply update their website experience at the time of the sales, to attract more users and convert these into buyers. Marketing and advertising tactics could also be improved by studying the data analytics thrown wide open in the open-source domain where billions of data points are available with regard to website traffic, the geographical distribution of users, their device usage, telecom operators, and app-based purchases.
As an extended phase, high-end data science projects for a resume in this particular domain could also involve extracting and analyzing data collected from email marketing and Click-based purchases.
Data Science Project
Your practical knowledge of data science operations can really impress the hiring manager during the interview. 7 out of 10 candidates with certified machine learning or data science degrees fail to meet the prerequisites of qualifying in a data science interview — practical experience.
The Open Source data community is a vast universe, and for new learners, the best possible territory to dive into. The challenges are far more complex than what you would find in the enterprise setup.
As masters of data science call it — It’s just like doing your own dirty laundry!”
Why choose open-source data sets?
Who doesn’t like it when the data is available for free and you can communicate with thousands of others in the same domain? Yes, that’s practically the best reason why open source data science project s are getting popular. These are free to use and modify inventories that have opened the floodgates on data science projects for freshers , many receiving sizeable funding and technical support from the likes of Google, IBM, Facebook, Amazon, Microsoft, and even WHO and NASA.
In fact, large scale data science project s are built on open science initiatives undertaken globally. These involve:
- World Bank
- Google Public Data Explorer
- EU Open Data portal
- Data.giv
- Kaggle
- Github
- IBM Redhat
- UNICEF and WHO open data
- LODUM, and so on.
Given the current COVID-19 scenario, a large number of Open Science projects have emerged that are exploring the ways and means to control the pandemic in high-risk areas. In India, over 500 data science project s have been funded to take care of various operations to improve these efforts:
- City-wise Patient Care Infrastructure database
- App-based monitoring and detection
- Labor migration and rehabilitation
- Vaccine trials and drug discovery
- Gene therapy
- Industry-wise projection of COVID-19 financial help
- Banking and insurance premium calculations in case of pandemic and other natural calamities
- Employee Workforce productivity measurement
- Work from Home automation data
- IT and Services management data
- Government aid and welfare scheme
- Drone-based facemask and PPP device monitoring
- IoT-based COVID-19 tracking
- Contactless eCommerce delivery management
- Contactless manufacturing of Food and Beverages, and so on.
You could say, learning data science and data engineering techniques today would not only qualify you for an aspiring career but also help you emerge as a forerunner in the quest to find a solution or solutions to many challenging problems arising from the COVID-19 pandemic.
Data Science Projects For Freshers Tips
Now that you have understood the world needs more data scientists and analysts to constantly work on complex issues and find real-world answers to these, here’s a quick checklist of tips you could as a fresher.
- Asking: Can I really Become a Data Scientist?
Most beginners squander at the opportunity of truly making a mark in the career as a data scientist. Nobody can become a data scientist in a single day, or for that matter with a single data science project . The key is to start exploring data science opportunities and constantly refining your open source data access and outcomes using cleaning techniques. The more targeted you are in your approach, the higher are your chances of understanding your data.
2. What are the other roles in data science?
According to LinkedIn’s data science jobs research, the top titles (size and CTC based) in the industry are:
- Data Engineer
- Business Intelligence Analyst
- AI and Machine Learning Programmer
- Data Architect
- Data Scientist
- Chief Data Officer / Chief Data Science Officer
3. What kind of skills does one need?
Impressive data science competencies and robust skills are required to get ahead in this massively disrupted and evolving space. Freshers should focus on technical, practical, and interpersonal skills. A mix of these skills, along with your work in open source data science project s could improve your chances of hitting your mark with your very first interview.
Technical Skills
- Coding and A/B testing with R, Python, SAS Analytics, Salesforce, Tableau, AWS, and Looker data sets
- Relational database and SQLs
- Basic understanding of Deep Learning, Machine Learning, and Augmented Learning principles
- Above-average technical expertise in handling any specialized application within Data Science — Cryptography, Software designing, Virtualization, Cloud and Edge Computing, NLP, Voice Search, Conversational AI, Chatbot designing, Telecall analytics, face recognition and biometrics, and so on.
Data Scientists seldom work alone. So, to qualify for your first job as a data science professional, you have to express your ability to work in a team and suggest leadership qualities that are key to brokering a relationship between your team members, business decision-makers, product owners, partners, and sometimes, even the press and media outlets. Good hold on written and verbal communication skills is a must to achieve success.
The best data science resumes invariably showcase the essence of strong technical, practical, and soft skills, planted with demonstrated ability to thrive under intense pressure, strict deadlines, and failure accountabilities.
Data Science Projects For Resumes
There are over a million possible data science projects for freshers . There’s still a lot happening in the world of Open AI, Blockchain, and Fintech at the time of me writing this guide for you. If you are a self starter and have a creative bend of mind, try exploring these topics as a readymade pedestal.
- Best TV Shows that were aired during the pandemic (volume of viewers, ad revenue, and screen time)
- Stock market analysis: Indian Stock market versus the US versus China and Japan
- Fake News detection and search engine reporting
- Instagram Influencer Celebrities’ audience data / followers base
- Air quality index of your city at various times and days of the week
- Energy management index of your city / state
- Birth control tools and products used versus medically / commercially available
- Marketing, sales, advertising and revenue generation indices of top 50 Indian or Chinese startups
- Crime against women index, and reporting data
- Cancer therapy data versus drug and diagnostic ratio, and so on.
As I pointed out, the eCommerce retail sale, telecom, and mobile networking data, social media intelligence, and email data remain the top destinations to try and test your abilities in data science projects in India . You can think about doing local analytics, and scale it to global levels as you start getting a hang of things in data science.
It’s all about finding the groove and sticking to basics, earning new skills and acquiring domain experience as you spend more time in the industry, and with leaders who understand how to predict and meet the upcoming demand.
The resource to know more
- https://www.analytixlabs.co.in/blog/how-to-learn-data-science-from-scratch/
- https://www.analytixlabs.co.in/blog/top-data-science-courses/
- https://www.analytixlabs.co.in/blog/what-is-data-science/
- https://www.analytixlabs.co.in/blog/how-to-become-a-data-scientist/
- https://www.analytixlabs.co.in/blog/python-skills-can-be-vital-for-a-successful-career-in-data-science/
- https://www.analytixlabs.co.in/blog/looking-beyond-covid-19-leverage-your-quarantine-time-to-invest-in-data-science-and-ai/
- https://www.analytixlabs.co.in/blog/data-science-can-be-for-everyone/
- https://www.analytixlabs.co.in/blog/7-data-science-deep-learning-projects-absolutely-learn/
Conclusion
If you are yet to apply for your first job interview, start building your Data Science projects for resumes . The easiest and smartest way to begin would be — “defining and redefining” your data science understanding, your audience (for whom you are solving the problem, and focusing on your data visualization and reporting skills. The novelty value is still a prized outcome of any data science project in India ; however, you should also aim your projects in data science towards cost optimization, price-cutting techniques, and employee experience trends. Those are sure shot ways to attract instant eyeballs of the hiring managers in the current industry.