A strong computer science, mathematics, or statistics background undoubtedly helps aspirants become successful data scientists; however, non-technical students can also become successful if they have the proper learning technique, motivation, education, and intense curiosity to seek relevant information about data science. Learning data science for non-IT and non-tech students can be challenging and complex as they have to learn from scratch. The right way to learn data science for non-IT students is to enroll in beginner-friendly data science courses that can help them to learn required data science skills like programming, deep learning, and statistical analysis. Anyone, irrespective of whether an IT student or non-IT student, can learn data science if they acquire business acumen, learn data science rules and technology, and learn how to work with large sets of data.
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How can non-IT students get into the competitive field of data science?
Data science certification course programs are available in the market today designed for mastering all the skills in a short period. There is a massive talent shortage and skill gap across diverse industries in the job profile of a data scientist. These course programs aim to fill the void between the demand and supply of skilled data science professionals. Data science makes it challenging for non-IT students to learn all the relevant skills and techniques in one go. However, with focus, a correct learning road map, and discipline, non-IT students can learn as well as master all the skills that are mentioned below.
- Mathematics and statistics
- Programming skills in Python, SQL, and R
- Deep learning and machine learning
- Business acumen and domain expertise
- Handling big data tools and frameworks such as Spark and Hadoop
- Communication, presentation, and storytelling skills
How can a non-IT student become a successful data scientist?
Even though a computer, mathematics, and statistics degree may help professionals land their dream job in data science, most recruiters and hiring managers look for technical skills and evaluate the knowledge base of the candidates to fill their emerging data scientist job role. The field of data science does not care whether you have a master’s or advanced degree. What matters is whether you can handle data effectively or not.
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The three skills sets required for non-IT students to master
If you are a non-IT student, you need to acquire the three vital data science skill sets, such as statistics, programming, or business acumen, to launch your data scientist career. Data science aspirants and practitioners must use their programming skills and business acumen to handle large data sets and convert raw data into actionable insights. It is essential for non-IT students to acquire a solid grasp of fundamental data science concepts, such as mathematics and statistics. Then they can evaluate the patterns and hidden trends in the data and perform data manipulation using different techniques. A complete understanding of data science and business fundamentals is essential to communicate your prediction and findings to the management team and help them make an informed and data-driven decision based on the insights derived. Even though you need diverse skills to excel in this data science domain, you need not be concerned, as most data scientists do not acquire all the skills and knowledge in their academic environment. This proves that the data science domain involves a self-learning process, which is advantageous for you if you are coming from a non-math, non-statistics, or non-computer science background.
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The fast track to becoming a successful data scientist
Offline and online boot camps and certification courses come with a mentally guided curriculum tailored for beginner data science students to learn about data science. With experienced data scientists and industry experts as mentors, you can learn how to handle accurate world data and solve critical business problems. These boot camps and certification courses are designed for novice data scientists without industry experience or a formal degree and help them get started in this tech domain. Enrolling in a data science certification course program will help you to acquire hands on learning and get a suitable employment opportunity at the end of the course. Unlike traditional educational degrees, these courses provide targeted learning, and if you can devote 15 to 20 hours of studies regularly, then you can keep pace with an IT student.
Proficiency in programming
Non-IT students must acquire proficiency in Python and R programming that will help them perform the job role of data scientists successfully. Data scientists use programming languages to solve statistical problems in the organization. Python and R programming languages come with a low learning curve, and you will find a plethora of online resources, courses, and books to acquire knowledge in programming languages.
Competent in using data science tools and technology
A non-IT student may find it challenging to learn about all the various tools and technologies in the data science market today. However, suppose they can acquire competency and skill set in the latest data science technologies like machine learning, extensive data querying, artificial intelligence, and deep learning. In that case, many job opportunities will open up in front of them. Moreover, once you have acquired the primary and intermediate knowledge about data science technologies, techniques, and software, you can slowly advance towards acquiring machine learning skills such as supervised and machine learning, reinforcement learning, applied detection, recommendation engine, survival analysis from a time series, neural networks etcetera.
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Data Science Placement Success Story
Ability to write as well as Execute complex queries
A good data scientist should be able to write and execute complex queries either by coding or with the help of coding and SQL database. They also have to be familiar with cloud tools, the Hadoop ecosystem, Apache Spark, etcetera. These data science tools and technologies help them to handle unstructured and complex datasets efficiently. Data scientists spend most of their time in programming or coding to complete a data science project. First, they must start learning programming languages and then gradually move to advanced and complex programming concepts. A consistent and focused approach lets you grasp all the programming and coding fundamentals within a few weeks.
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Conclusion
Non-IT students who want to make their career in the field of data science need to acquire proficiency in technical and soft skills to stay relevant in the market. The career field of data science is promising and comes with high salaries and a lucrative career path. Although it may initially feel overwhelming to grasp all the fundamental concepts, with dedication and focus, you can position yourself in this field within a few months only.
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Address – Ground Floor, Dhwarco Business Center, Plot 21B, 5th Cross St, South Phase, Guindy Industrial Estate, Guindy, Chennai, Tamil Nadu 600116
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