A crash course in data science for beginners

It is the backbone of tech-savvy businesses. Economist magazine called it ‘the oil of the digital era’. If you can figure out how to mine it, you’ve struck gold. 

Big data is revolutionising the world as we know it. It is big money. Tech giants like Facebook/Meta and Amazon have earned their multi-billion dollar revenue from learning how to monetise digital data using artificial intelligence. The rest of the world is following suit. Everyone is jumping on the bandwagon and finding ways to profit from statistical data science. This has opened up a ton of exciting opportunities for you. 

As a data scientist, you are in a unique position of power. You have the expertise to take raw data and convert it into big bucks. It’s new-age, economic alchemy. 

The future of business is heading in this direction. And you are in the driver’s seat. 

What does a data scientist do? 

Data science is an emerging, research-based field that is fast becoming one of the hottest careers around. It is a vital instrument that helps businesses grow and evolve. Data scientists, analysts and engineers know how to use the information productively and innovatively. They can identify the important bits of data, generate insights and use them effectively to create sustainable solutions. They extract value from a large body of information by using state-of-the-art technological methods. They make informed business decisions for industries like banking, retail, IT, healthcare, real estate and many more. By using intricate quantitative algorithms, they create productive strategies.

Sounds complicated? Not if you are a skilled and qualified professional with the right combination of technical and soft skills. If you have a data science certification, you are a valuable addition to any company. 

Job profiles 

Ready to take a deep dive into big data? Here are some of your options:

Data scientist 

You are the brains behind the operation. From understanding the business perspective to data collection to building complex models and simulations, you have your fingers in every pie. Your speciality is maths and statistics, but eventually, you will lead a team of professionals with specific skills. 

Big data analyst 

You are responsible for a variety of tasks. One of the more important ones is data visualisation, where you present facts and figures in a visual context using charts and graphs. You will also work with data scientists to simplify and update different services and data processes.

Data science engineer

You are in charge of setting up the frameworks that help data scientists create their algorithms. You use tools to optimise and format the collected information and ensure it is ready for further processing. 

Business intelligence professional 

You are working for companies that need your valuable insights to improve their profits and productivity while enhancing their performance. You know how to efficiently manage data to achieve your goals. 

The data science prerequisites 

You need to possess the required abilities to qualify as a data scientist. A data science course from a reputed institute offers students a detailed syllabus that teaches the necessary technical skills, programming languages and scientific methodologies. You can opt for a certificate course in data analytics or do a more intensive PG program in data science. Here are some of the skills you need to get a job in this industry.

Technical skills:

#1 A working knowledge of maths and statistics

You need a good head for numbers if you want to be in this line of work. Algorithms, technologies and machine learning methods require a strong understanding of mathematics. Statistics is a useful method to study current or emerging trends and patterns and find ways to adapt to them. 

#2 Programming languages 

Do you speak data? Then you must be proficient in Python, R, SQL, SAS, Java and other forms of programming languages. Being conversant in tech talk is important as many applications, methods and tools are written in software code. 

#3 Analytical tools 

It is your job to unravel meaning from unstructured data. You are going to need some assistance with that. Data analytical tools such as Microsoft Excel, Tableau, Hive, Spark and Hadoop are used in big data analytics to help streamline and optimise processes. 

#4 Machine learning 

A sub-section of artificial intelligence, machine learning uses algorithms to understand and mimic the way people learn. This can be highly useful to uncover insights and make predictions about future trends. 

#5 Deep Learning 

This is a more enhanced form of machine learning. The deep learning tool can take huge amounts of raw, unprocessed data and categorise them efficiently. This tool has led to the creation of virtual assistants. 

Life skills: 

#1 Problem-solving capabilities 

When a company faces an obstacle or a challenge, it is up to you to figure out a feasible solution using data science. However, it helps if you have a sharp mind that can weed out the issues and focus on ways to overcome roadblocks. 

#2 Good communication skills

So you have a fantastic insight on improving sales and boosting customer loyalty in your company? Well done. Now you have to communicate your ideas to your team or department heads. If you can fluently and articulately convey your thoughts, you have the makings of a competent analytic specialist. 

#3 Attention to detail 

In a sea of endless information, it is easy to miss a coding mistake or a human error. This can cause serious implications. A detail-oriented professional will be able to save the company time and money. Similarly, an important detail could go unnoticed unless spotted by an eagle-eyed individual with a knack for accuracy and precision. 

#4 A curious nature

Analysts want to delve deeper below the surface. It’s in their nature. They are naturally inquisitive about the ‘why’ and ‘how’ of things. This is a significant advantage that ensures you maintain a high-quality standard when generating insights. 

The forecast for data science? The future is looking bright!

Since big data has taken the world by storm, data scientists have become increasingly headhunted by all major companies. A prospective candidate with the right combination of skills and academic qualifications can go a long way in any industry. So what can you expect from your career? Let’s investigate further.

Job opportunities

It’s the next big thing in careers. Suddenly every company wants a data analyst team. Organisations have realised the merits of big data and the impact it can have on their future. This is a global phenomenon. Different industries and business sectors around the world are actively looking for certified professionals. Together, you can help them make transformative changes and educated decisions. It can lead to leadership roles within the company along with exciting opportunities to grow professionally. There are so many branches and divisions in this business, you can grow laterally as well. If you’re a professional with a degree in business administration, engineering or IT, a data science certification can open up new opportunities or enhance your existing career. It can be a stepping stone to other possibilities like opening up your own company or being a high-ranking consultant with a multinational corporation. 

Salary expectations

Nearly 46 per cent of data scientists earn between 6 to 15 lakhs a year. As you gain more experience and expertise, that figure will increase. Freshers generally earn around 5 to 6 lakhs per annum while more established analysts can take home a salary that ranges from 25 lakhs to a crore. The salaries vary according to the company, location and job profile. Rest assured, this is a rewarding profession that can lead to a prosperous 

Conclusion

There you have it. A quick view of one of the most in-demand fields, and how you can be a part of it. Data science is here to stay. In fact, as technology advances, big data will get even more lucrative. So if you want a lasting career that is filled with many possibilities, you know what to do next. 

Click here for one of the best data analysis courses for beginners