A 4-year degree in Data Science is provided by IIT-Madras; JEE eligibility is not necessary
One of the most anticipated admission tests in India is JEE. Numerous students want to pass this test since doing so can greatly advance their engineering careers. You can be accepted into one of India’s most prominent IIT institutes by succeeding in JEE. However, the number of students that show up for tests compared to the number of seats offered is not particularly realistic. Despite their best efforts, many students might not be able to get the specific score needed to secure a place. However, there is still time for you to pursue your passions; the world is not over. If you are unable to pass the JEE, you have several possibilities.
The Indian Institute of Technology Madras (IIT Madras) recently announced that its BSc in Programming and Data Science would have an option for a four-year BS Degree in Data Science and Applications due to “strong demand from the students.” Students may do an 8-month apprenticeship or a project with businesses or research organizations as part of their BS degree.
According to IIT-Madras, this program is created to give students a variety of entrance and departure points where they can obtain a certificate, diploma, or degree. This gives students flexibility and gives them the freedom to decide what they want to get out of the program.
Students presently enrolled in Class 12 may also apply and be accepted into the program. Those who are admitted will begin the program once they have completed Class 12. Any stream of students may enroll. No age restriction applies. Anyone who completed Math and English in Class 10 is qualified to apply. There is no regional restriction because the lessons are offered online. More than 13,000 students are now enrolled in the program, with Tamil Nadu having the highest proportion, followed by Maharashtra and Uttar Pradesh. In 111 cities around India, there are 116 testing locations where in-person tests are given. Additionally, the U.A.E., Bahrain, Kuwait, and Sri Lanka now have test centers available.
IIT Madras Director Prof. V. Kamakoti stated, “The institute is pleased to provide this well-designed, modern BS in Data Science and Applications degree, providing access to IIT quality education in an accessible way to learners across the country. Data Science is one of the hot subjects right now. This curriculum places a strong emphasis on employment in a field where there is a considerable need for qualified personnel.”
Students will learn data management techniques, how to visualize patterns for managerial insights, how to model uncertainties, and how to develop models that help with forecasting so they can make wise business decisions. The students receive substantial hands-on training as well as experience learning to prepare them to meet industry requirements. In addition, IIT Madras helps students who have finished the diploma level of the program find internships and jobs.
Prof. Andrew Thangaraj, professor in charge of the BS in Data Science and Applications at IIT Madras, elaborated on the motivations for this new endeavor. “Since Data Science is a multidisciplinary field, this BS degree from IIT Madras is available to students from all backgrounds,” he added. IIT Madras offers degrees in the humanities and commerce to its students as well. This degree may be completed while attending an on-campus program or while holding a full-time job because the course material is delivered online and the in-person tests are held on Sundays.
Through this ground-breaking approach, students can attend IIT Madras without taking the very competitive Joint Entrance Examination (JEE). This immediately assists the underprivileged students from remote regions who would otherwise find it difficult to join JEE coaching programs. The program also provides eligible students with financial needs with up to 100% scholarships.
Additionally, Dr. Vignesh Muthuvijayan, Professor In-Charge of the BS in Data Science and Applications at the Indian Institute of Technology Madras, stated that admission to the program is not dependent on passing the JEE. In contrast to other admission exams, this program’s qualification procedure is more broad-based. IIT Madras can admit all competent applicants without any numerical restrictions because of its cutting-edge pedagogy. IIT Madras has developed one of the most inclusive models in the nation with the help of significant scholarships.
The BS program at IIT Madras will serve as a foundation for producing knowledgeable and marketable professionals in a data-driven environment. The IIT Madras team is sure that this inclusive and cost-effective educational paradigm would greatly increase the reach of IITs and meet the urgent need of students for access to a top-notch education.
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Top 10 Data Science Penny Stocks To Buy Below US$100 In 2022
Among thousands of data science stocks, here are the top 10 listed data science penny stocks for you
Tech investors are highly overwhelmed with the advancement in products and services through the implementation of cutting-edge technologies. They want to invest in tech stocks related to reputed and emerging technology companies to earn profit with the utmost stability and flexibility. As we know, data science is gaining immense popularity in industries across the world for its effective data management. Data science companies are thriving in the tech market to cultivate real-time data and transform it into meaningful and in-depth insights. Thus, this is leading to the huge demand for data science stocks offered by data science companies. There are thousands of data science stocks but let’s explore some of the top 10 data science penny stocks to buy below US$100 in 2022 for smart investment.
Current price: US$75.75
Workiva, Inc. is one of the top penny data science stocks for providing cloud-based compliance and regulatory reporting solutions for industries across the world. The data science company is known for offering the Workiva platform to offer controlled collaboration, data integrations, data linking, process management, and many more from enterprise resource planning, human capital management, and so on.
New Relic, Inc.
Current price: US$69.00
New Relic, Inc. is a SaaS and penny data science stock company offering a wide range of products for effective data management and different data types. It includes an extensible cloud-based platform such as New Relic One Platform, New Relic Application Performance Monitoring, New Relic Applied Intelligence, and many more. This stock of data science is focused on providing open data application performance interfaces, open-source connectors, big data databases, and so on for customers across the world.
Current price: US$88.22
Elastic N.V. is focused on delivering cutting-edge technology to search through a vast amount of real-time data such as structured and unstructured data for multiple applications. It has a wide range of data science products and services such as Elastic Stack, Kibana, Beats, Elastic Agent, Elasticsearch, and many more. It offers a data processing pipeline for ingesting data efficiently into specific areas.
Current price: US$9.59
Palantir Technologies can deploy software platforms for assisting in counterterrorism investigations and operations. The data science company offers Palantir Gotham to allow users for identifying patterns in real-time data sets. The data science stock offers a wide range of products such as Palantir Foundry and many more to integrate data collection and data analysis efficiently.
Current price: US$35.68
Teradata Corporation is providing a connected multi-cloud data platform for enterprise analytics. The stock of data science is known for offering Teradata Vantage which allows other companies to leverage real-time and connect multiple sources to adopt digital transformation through an integrated migration.
Current price: US$33.90
Domo, Inc. is popular for operating as a cloud-based platform in the US. The platform is known for digitally connecting the CEO to an employee with people, data, and systems. There is access to real-time data and meaningful in-depth insights for effective data management.
Thoughtworks Holding, Inc.
Current price: US$17.27
Thoughtworks Holding, Inc., is a well-known data science stock to offer technology services and data and artificial intelligence services to the global tech market. The services include data strategy, data platforms, data mesh, data governance, digital transformation, and many more. The data science stock is focused on serving industries such as energy, healthcare, retail, financial services, travel and transportation, and the automotive industry.
WNS (Holdings) Ltd.
Current price: US$87.45
WNS (Holdings) Ltd. is known as a popular data science company stock to offer data, voice, and analytics services across the world. This data science company stock operates through two segments WNS Global BPM as well as WNS Auto Claims BPM. It offers transformation services to industries such as retail, manufacturing, healthcare, etc.
Current Price: US$16
A data cloud company known for its services in data analytics and management products across the globe. They help companies with real-time insights to deal with transformational use cases effortlessly. An NYSE-listed company with a trailing 12-month revenue of US$904.8 million holds the highest intraday current value at US$16.
Current Price: US$67.84
It is an end-to-end data analytics company whose specialized services include creating visual workflows in addition to regular data analytics functions like data profiling, preparation, blending, etc. A collaborative platform to share insights among the departments to devise simple and agile data models.
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How Does Data Science Unleash The Value Of Your Legal Information?
Data science gives people the ability to make knowledgeable, data-driven business decisions
Corporate legal management solutions enable legal departments to gather a tonne of information about their legal operations. The systems that the legal department uses to conduct business are used to record information regarding transactions, open matters, matter history, the functioning of outside counsel, and many other aspects of the department’s operations. Even while this data can offer crucial insights that aid the department in operating more productively, affordably, and efficiently, those data insights must first be accessed. The secret to unlocking the full potential of the gathered data is data science.
Why is data science important?
In the subject of business known as data science, knowledge and insights are derived from noisy data using scientific methods, procedures, algorithms, and systems. With the use of data science, it is possible to extract useful knowledge and understanding from data points. Despite its apparent technicality, it actually gives people the ability to make knowledgeable, data-driven business decisions.
Modern machine learning and artificial intelligence (AI) technologies are sophisticated enough to handle vast amounts of data and produce insightful results. Some of the solutions used by corporate legal departments and insurance claims divisions to help their strategic decision-making incorporate these technologies.
By utilising data science, legal and claims divisions can greatly enhance internal procedures and workflows and standardise the data they collect to ensure that their choices are based on facts rather than gut feelings.
How to Find the Expertise?
In order to use data science to maximise the value of the information that you collect, the appropriate knowledge and experience are essential. The majority of firms, however, do not have a group of data scientists on hand to establish a centre of excellence in data science to create AI algorithms and address challenging issues. Therefore, it is essential for the majority of businesses to collaborate with a supplier who can supply the required expertise and technology.
To successfully transform your data into actionable decisions and beneficial business consequences, a data science provider should have the following three types of expertise on its team:
- Experts in process design consult with you and your team to identify any areas of your work that are particularly challenging or don’t function as intended. They also come up with solutions to these problems. These professionals are very empathic and perceptive when it comes to the conditions necessary to streamline and lessen the complexity of operations. They are also experts in customer service and user interfaces.
- To create the specifications for the AI model, domain experts collaborate closely with process design specialists. They combine client feedback with their understanding of industry best practises doing this. Additionally, data is properly labelled by domain experts to aid in the creation of a unique AI model.
- Based on the requirements of the client, data scientists translate data sets and build an appropriate AI model with the necessary features. Data scientists must fully comprehend the client’s requirements in order to avoid starting with a predetermined, one-size-fits-all AI solution. Data scientists have knowledge in UI/UX design and are strategic design gurus.
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Top 5 Ways Data Science Is Different From Decision Science
Analyzing data is not something only data scientists do. Analysts, researchers, growth marketers, and decision scientists often have to dig into data to find solutions to business problems through meaningful insights. Quite often organizations have both data scientists, and decision scientists and that creates confusion as to who’s responsible for what. Those who are venturing out to learn data science should have a prior understanding of what they want to learn. The following are the 5 key differences between data science and decision science.
- Data science considers data as a tool for enhancing and developing new products with different statistical methods. Decision science considers data as a tool to make smart decisions for the benefit of a company.
- Data science seeks meaningful insights for the company executives. Decision science takes a 360 view to make insights usable for the company.
- Data science needs only analytical ability whereas decision science demands both analytical ability and business acumen.
- Data science integrates mathematics and technology with data visualization and mathematical computation. Decision science is the interdisciplinary application of mathematics, technology, and business with behavioural science.
- One of the challenges of data science is the supply of a huge amount of dirty data whereas one of the challenges of decision science is the lack of reliable data.
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