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Home / Blog / Data Science / A Beginner’s Guide to Data Science in Malaysia
Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of AiSPRY and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 18+ years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.
Table of Content
Data science is the use of raw data and the application of probability, analytics, and statistics to recorded data in order to make critical business decisions. This provides students with important insights into the future of business through the examination of the data. Malaysia is one of the best countries in the world to study data science. There are several distinguished, well-known colleges that provide data science courses. In addition to machine learning and artificial intelligence, data science also comprises several tools for data analysis. It might be useful to infer certain trends and patterns from the data. To predict future trends, a data scientist also employs sophisticated algorithms, machine learning, and data engineering.
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A normal Data Analyst also analyzes the data, but Data Scientist is different from Analyst. A Data Analyst generally explains the recorded data and takes business decisions according to it. But Data Scientist includes exploratory analysis of data, Machine Learning and advanced algorithms and Data Engineering to predict future trends. There are many ways to predict data trends and patterns, some of the ways followed are:
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It has been shown that many people find it challenging to make decisions these days. We rely on statistics to make decisions for us because we lack the capacity to do so. Data science uses algorithms, machine learning, and artificial intelligence to forecast patterns and trends based on historical data. Many pieces of data are simplified, which facilitates decision-making. Making important decisions for your business is also aided by it.
Knowing what Data Science is in its most basic form is the first step for a student on the path to becoming a data scientist. It combines a variety of abilities.
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Analytical maths is crucial while discussing data science. You must be well-versed in probability and statistics. Additionally, learning linear algebra is advisable. The foundation of machine learning is based on statistics, which involves laborious mathematical calculations.
Learning a programming language becomes essential when you study at a Data Science course. If you are not familiar with programming, then Python is the best available option for you. Python is the easiest programming language to learn as its syntax is relatively easier than other programming languages. It copes with the demands of specialists and it is also multifunctional.
Machine learning assists in teaching computers to make their own judgements and act on their own. In order to provide robots the ability to make decisions, algorithms are used. By creating machine learning, we can eliminate the need for repetitively writing precise instructions.
Data visualization refers to helping people to get the importance of data by visualizing the data in a context that is visible to people.
Data mining is about finding hidden patterns and trends of data according to categories of information; algorithms are used to facilitate low-cost business decisions. It also helps to increase revenue for the business.
Gaining experience in the real world is just as vital as mastering theories. To become an expert in data science, you need a lot of practise. You may participate in many hackathons to improve your technical and coding abilities. For practise, there are a lot of free data sets accessible. You can also gain knowledge through the accomplishments of others.
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After you have followed these five steps, you can start applying for jobs. You can participate in competitions that may secure you a very charismatic opportunity for a job. This can also help you in checking your capabilities and skills. GitHub provides the platform to publish programs on data analysis. It can get you acquainted with your potential employers. By publishing your work, you can showcase your capabilities and skills.
These are some of the procedures that might help you succeed in the Data Science industry. One thing, nevertheless, should be kept in mind. In order to succeed in data science, you need to be committed and put in a lot of effort. Make sure learning data science is something you actually want to do. Learn it for the right reasons rather than merely because it is fashionable and a well-known field. The stages listed above can be used as a roadmap for your data science journey. Expecting to obtain everything in a month or a year is unrealistic. It will take some time to comprehend all of this because it is a step-by-step procedure. Learn the material with determination and drive, and finish the Data Science training successfully.
360DigiTMG - Data Science, IR 4.0, AI, Machine Learning Training in Malaysia
Level 16, 1 Sentral, Jalan Stesen Sentral 5, Kuala Lumpur Sentral, 50470 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
+60 19-383 1378
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