There are tons of courses available which are short-term as well as long-term etc that one can pursue to make a career in the field. Here in this article, we will get to know about the Data Science Course Details: Eligibility Criteria, Scope and Top Colleges for Admission etc and more. There are many students who are actually looking for a career in the field of data science but due to their lack of knowledge, there are unable to opt for the course. Here we will share with you the complete details about the course that one needs to know before entering the course.
Table of Content
Data Science Course Details:
Data science is outlined as a mix of arithmetic, business acumen, tools, algorithms and machine learning techniques, all of that facilitate us to find out the hidden insights or patterns from Data which might be of major use within the formation of massive business selections.
In Data Science, one deals with each structured and unstructured Data. The algorithms additionally involve prognostic analytics in them. Thus, Data science is all about the current and future. That is, checking out the trends supported by historical Data which may be helpful for gift selections and finding patterns which might be modelled and may be used for predictions to ascertain what things may appear as if within the future.
Data Science is a uniting of Statistics, Tools and Business data. So, it becomes imperative for a person to possess sensible Data and an understanding of those. Now let’s see the Data Science Course Details about the Why to learn this course as per the current market condition.
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Why learn Data Science:
With the number of Data that’s being generated and therefore the evolution within the field of Analytics, Data Science has clothed to be a necessity for firms. to create the most out of their Data, firms from all domains, be it Finance, Marketing, Retail, IT or Bank. All are searching for Data Scientists. This has a junction rectifier to a large demand for Data Scientists everywhere in the world. With the sort of pay that a corporation must supply and IBM declaring it as the trending job of the 21st century, it’s a moneymaking job for several. This field is specified anyone from any background will build a career as a Data person.
Components of Data Science:
Data Science consists of three components that are considered to be important. Here are the details about the three major components of Data Science:
Machine Learning: Machine Learning involves algorithms and mathematical models, in the main utilized to create machines to learn and prepare them to adapt to everyday advancements. As an example, these days, statistic prognostication is incredibly lot in use in commerce and monetary systems. In this, supported historical Data patterns, the machine will predict the outcomes for the longer term months or years. this can be an application of machine learning.
Big Data: Every day, humans are manufacturing such a lot of Data within the kind of clicks, orders, videos, images, comments, articles, RSS Feeds etc. These Data are usually unstructured and are commonly known as massive Data. massive Data tools and techniques chiefly facilitate changing this unstructured Data into a structured kind. as an example, suppose somebody needs to trace the costs of various products on e-commerce sites. He/she will access the info of a similar product from totally different websites exploitation net Apis and RSS Feeds. Then convert them into structured kinds.
Business Intelligence: Every business has and produces an excessive amount of data each day. This Data once analysed fastidiously and so given in visual reports involving graphs, will bring the sensible higher cognitive process to life. this could facilitate the management in taking the most effective call once fastidiously delving into patterns and details the reports bring back to life.
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Skills and Tools needed to learn:
- In-depth data in R: R is employed for Data analysis, as an artificial language, as AN setting for applied math analysis, Data visual image
- Python coding: Python is the majorly most popular to implement mathematical models and ideas as a result of python has made libraries/packages to make and deploy models.
- MS stand out: Microsoft Excel is taken into account a basic demand for all Data entry jobs. it’s of nice use in Data analysis, applying formulae, equations, and diagrams out of an untidy heap of Data.
- Hadoop Platform: it’s AN open supply distributed process framework. it’s used for managing the process and storage of massive Data applications.
- SQL database/coding: it’s chiefly used for the preparation and extraction of datasets. It may be used for issues like Graph and Network Analysis, Search behaviour, fraud detection etc.
- Technology: Since there’s such a lot of unstructured Data out there, one additionally ought to Data to access that Data. this could be tried in a range of ways, via APIs, or via net servers.
Techniques:
- Mathematical Expertise: Data scientists additionally work on machine learning algorithms like regression, clustering, statistic etc that need an awfully high quantity of mathematical data since they themselves are supported mathematical algorithms.
- Working with unstructured data: Since most of the info created each day, within the kind of pictures, comments, tweets, search history etc is unstructured, it’s an awfully helpful talent in today’s market to understand the way to convert this unstructured into a structured kind and so operating with them.
Business Understanding:
- Business Acumen: Analytics Professionals are available the mid-management to high-management within the hierarchy. So, having business data comes as an enormous demand for them.
Data Science Course Details: Eligibility Criteria
To become a Data Scientist, a student should have a college boy or postgraduate degree in Data Science or connected fields like Computer Science, Machine Learning, Engineering Science, Arithmetic, Statistics, etc. Students should check the eligibility criteria for various Data Science courses before enrollment.
There are many programs is being offered, and the required criteria for the program are different for each program. Here are the details about the Data Science Course Details Eligibility Criteria:
| Course | Data Science Course Eligibility | Duration |
| Diploma in Data Science | Graduation in Science or Engineering with 50% marks from any government-recognized Institute with Maths/Statistics/CS/IT as one of the core subjects. | 1 year |
| Undergraduate Data Science Programs (BSc/BTech Data Science) | 50 – 60% marks in class 10+2 exams & basic knowledge of Statistics, Mathematics, and Programming. | 4 years |
| Postgraduate Data Science Programs (MSc/MTech Data Science) | Graduation in Science or Engineering with 55% – 70% aggregate. Intermediate knowledge of Statistics, Mathematics, and Programming. In some cases, work experience is also required. | 2 years |
Data Science Course Syllabus
The syllabus for data science can be categorized into 4 major blocks i.e.
- Programming Languages: Python & R
- Machine Learning, Mathematics, Statistics
- Natural Language Processing (NLP)
- Big Data Analytics
Note: This is a common list of data science subjects. To check the complete data science syllabus course-wise; check the Data Science Course Syllabus article.
| Category | Subjects/Skills |
| Programming Languages: Python & R | Data Handling, Data Manipulation, Data Wrangling, Data Visualization |
| Machine Learning, Mathematics, Statistics | Statistical Concepts, Data Modeling, Statistical Analysis |
| Natural Language Processing (NLP) | Handling Unstructured Data, Text Classification |
| Big Data Analytics | Relationship Database Management, Big Data Ecosystem, PySpark, NoSQL Database, Cloud Computing, Hadoop, Spark |
The Syllabus can be different as per the course and its duration. On average, it is the basic component that you will be studying in the Data Science Course Details Syllabus.
Career Scope and Job Opportunities:
A career in data science has become one of the highest-paid professions. According to Analytics India Magazine, the average salary of a data scientist is INR 10 lakhs annually. More than 1200 data scientists in India earn more than INR 1 crore annually.
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Top Careers in Data Science:
The top careers in data science are data scientists, machine learning engineers, data engineers, statisticians, etc.
| Job Profile | Average Annual Salary |
| Data Scientist | INR 7- 8 lakhs |
| Application Architect | INR 4 – 6 lakhs |
| Business Intelligence Developer | INR 4.5 – 6.5 lakhs |
| Machine Learning Engineer | INR 5 – 11 lakhs |
| Data Architect | INR 7 – 10 lakhs |
| Clinical Data Scientist | INR 3 – 6 lakhs |
| Machine Learning Scientists | INR 6 lakhs |
| Statistician | INR 5.34 lakhs |
| Actuarial Scientist | INR 10 lakhs |
| Mathematician | INR 9 lakhs |
| Data Engineer | INR 8 lakhs |
| Software Developer Analyst | INR 5.75 lakhs |
Data Science Companies:
The top data science companies worldwide and the average salary they offer for different data science job profiles are mentioned below.
| Company | Average Data Scientist Salary (Annually) |
| Mercedes Benz Research and Development | INR 12.99 lakhs |
| JP Morgan | INR 19.35 lakhs |
| Paytm | INR 8 lakhs |
| Boston Consulting Group | INR 22.80 lakhs |
| Airtel X Labs | INR 21 lakhs – INR 27 lakhs |
| Oracle | INR 12.21 lakhs |
| PayPal | INR 18.78 lakhs |
It is not tough to make a career in the field of Data Science after the completion of the course. There is too much scope in this field. One just has to join a better institute and gain the right knowledge about the course. So, this is the complete Data Science Course Details. Hope it was useful to you.
