Data Science is a combination of machine learning, mathematics, tools, algorithms, and business acumen approaches that aid in the discovery of hidden insights or patterns in raw data that can be useful in the creation of key business decisions.
In data science, both structured and unstructured data are dealt with. Predictive analytics is also used in algorithms. As a result, data science is concerned with the present and future. That is, identifying trends based on previous data that can be valuable for current decisions, as well as identifying patterns that can be modeled and used to anticipate how things will look in the future.
Statistics, tools, and business knowledge are all combined in Data Science. As a result, a Data Scientist's knowledge and comprehension of these topics are critical.
Why Study Data Science in the First Place?
Data Science has become a necessity for businesses as a result of the massive amounts of data being generated and the advancements in the field of analytics. Companies from many disciplines, including finance, marketing, retail, IT, and banking, are attempting to make the most of their data. All of them are on the lookout for data scientists. As a result, Data Scientists are in high demand around the world. It is a lucrative career for many because of the kind of salary that a corporation may offer, and IBM has declared it as a trending job of the twenty-first century. Data Scientists can work in any industry and come from any background.
Required Qualifications
To become a data scientist, you'll need the following skills:
Tools
1. Thorough understanding of R: R is used for data analysis, as a programming language, as a statistical analysis environment, and for data visualization.
2. Python coding: Python is widely used to implement mathematical models and concepts since it has a large number of libraries and packages that can be used to create and deploy models.
3. Microsoft Excel: Microsoft Excel is a must-have for any data entry job. It comes particularly handy when working with large amounts of data and applying formulae, equations, and diagrams.
4. Hadoop Platform: Hadoop is a distributed processing framework that is open source. It's used to keep track of how large data applications are processed and stored.
5. SQL database/coding: SQL database/coding is mostly utilized for dataset preparation and extraction. It can also be utilized to solve issues such as graph and network analysis, search behavior, fraud detection, and so on.
6. Technology: With so much unstructured data available, it's important to know how to access it. This can be accomplished in a variety of ways, including through APIs and web servers.
Techniques
1. Expertise in Mathematics: Data scientists also deal with machine learning techniques such as regression, clustering, and time series analysis, all of which demand a high level of mathematical expertise because they are based on mathematical procedures.
2. Working with unstructured data: Because much of the data produced every day is unstructured, such as photographs, comments, tweets, search history, and so on, knowing how to convert this unstructured data into a structured form and then working with it is a very useful ability in today's market.
Business Understanding
1. Business Acumen: Analytics Professionals are found at all levels of the organization, from mid-management to high-management. As a result, having business expertise is a must for them.
Where to pursue a Master’s Degree in Data Science?
Right now, data science is a fantastic field to get into. The demand for these jobs is great, and so are the wages. While a bachelor's degree can earn you solid entry-level (and even some mid-level) data science positions, a master's degree will help you to expand your career options.
If you are interested in the field and have all the necessary skills required to enroll in the Master’s program, you can pursue it from Univ.AI which offers the best Online Master’s in Data Science programs.
Univ.AI offers a variety of AI and machine learning certificate programs, all of which are designed to provide meaningful learning and professional outcomes at various stages of your learning journey. We also provide free short preparatory courses to help you learn the fundamentals and prepare for our programs. All of our programs are delivered LIVE online with extensive mentoring and a strong emphasis on hands-on learning.
This 29-week program offers you a broad and deep understanding of Machine Learning (ML) and Artificial Intelligence (AI) through three core courses and one optional elective course (up to 5 weeks) (AI).
The training begins with essential Machine Learning and Data Science skills. Advanced Modules build on this foundation, allowing you to gain a strong understanding of Data Science and Engineering, encompassing large data, databases, cluster development, and high-performance applications. You'll also use what you've learned in tough module-end projects.
Program Fee: ₹2,35,000
Program Outcomes: You'll be an expert at creating cutting-edge Data Science and AI apps with complicated embedded models and cutting-edge AI pipelines once you've completed this course. Exceptional performers (those who receive an "A") are guaranteed a position in a top-tier organization with cutting-edge technology.
Scholarship: Students who are enrolled full-time in academic programs and will graduate in more than 9 months may be eligible for a scholarship based on documented need. Please specify in the tuition section of your application that you want to be considered for a scholarship.
Just keep in mind that learning never stops. Obtaining a master's degree in data science will undoubtedly prepare you for high-level data science work in the near and long term. So sign up for Univ.AI's Data Science certification right away!