Why BTech In Data Science And Artificial Intelligence Is Becoming The First Choice After 12th Science

Introduction

What courses after 12^th Science? This is the common thought that many of the students have in their minds once they complete their 10th board exam. It is the major question to almost any student in any country. Owing to the availability of numerous options, choosing the right one becomes a tough decision.

Looking at the career growth opportunities, many students are inclined to pursue B.Tech in Data Science and Artificial Intelligence. Both data science and AI have immense capabilities that are expected to bring lucrative career opportunities and phenomenal growth for a student. This article tells you more about what makes data science and AI so appealing to students after 12^th.

About Artificial Intelligence

Artificial Intelligence is a field of engineering that is all about developing computer systems to perform tasks that would generally need human intelligence. These include robotics, game playing, computer vision, speech identification machine, language detection systems, expert systems, and many more.

Artificial Intelligence is arguably the highly transformative technologies available for humans. Its use is not just limited to the development of computers, mobiles, etc. It helps build computer machines that are equipped with human intelligence. It is widely used in visual perception, forming decisions, recognizing speech, and translating between different languages.

What Is The Scope Of Artificial Intelligence?

In the past, machine learning and AI technologies have moved people ahead in technology stakes rapidly than what they have imagined. The demand for AI and machine learning professionals is increasing every day, and it is estimated to stay in the future as well.

AI solutions have a key positive impact on various critical domains that includes weather prediction, soil and crop management, healthcare, security, surveillance, and defense. Robust and long-term solutions to problems need a methodical and well-organized approach that is ingrained in the basics of Artificial Intelligence.

Artificial Intelligence is widely used in various industries to develop software that aims to solve problems and realize goals. A career in this field exponentially fulfills the requirements of digitally transformed industries.

There is no dearth of career opportunities for AI qualified, skilled candidates. When compared to the present demand vs. supply in this sector, we can see that there is a substantial shortage of expert tech talent who possess the essential skills. Over the past three years, the employment sector witnesses an increase in AI jobs by more than 121 percent.

These employment opportunities are released in public and private sectors in the areas of game programmer, computer scientist, data scientist, Research Scientist, Robotic Scientist, Big Data Engineer Or Architect Software Engineer, Business Intelligence Developer, etc.

Academic Requirements for Careers in AI

The demand for professionals who are skilled in this field exceeds the present supply. The BTech program in Artificial Intelligence is a step towards addressing this extremely slanted demand and supply scenario.

A person who wants to enroll in AI courses needs to study mathematics to gain mathematical logic. You should get a good idea of biology and physics. It is also essential to gain knowledge about human psychology and physiology to understand the biological approaches to AI.

Learn about programming languages such as Lisp, Prolog, and C. It is good to master basic machine languages. This is essential as the job prospects depend on the languages that are currently running in fashion.  Bachelor’s degree is the road to get into entry-level positions in Artificial Intelligence.

It is advised to sign up for the below courses:

• Bayesian networking (that includes neural nets)
• Computer science (to get experience in coding with key programming languages)
• Engineering
• Cognitive science theory
• Robotics
• Physics with various components of maths (calculus, algebra, algorithms, logic, statistics, and probability)

It is quite easy for a software engineer to become an AI developer with some AI-focused courses. You can also take a few AI online or offline courses to boost your chances of employment.

Job Positions For An AI Specialist

There are multiple career options available to a skilled and competent AI. A student who completes his bachelor’s degree (B.Tech.) in this subject can occupy the following positions.  

1. Machine Learning Engineer

This is the highly sought position that every AI professional wishes to secure. People who work in this position are responsible for building and managing platforms for machine learning projects. The major tasks of a machine-level engineer involve applying predictive models and influencing natural language processing when working with massive datasets.

This field is ideal for people who come from a background in data science and applied research. To get this position, it is required for a candidate to be an AI programmer. This demonstrates an in-depth understanding of several types of programming languages. They should be well-versed in agile development practices and highly experienced with leading software development tools such as IntelliJ and Eclipse.

Applicants should show an expertise working knowledge of conventional programming languages such as Python, Java, and Scala.  Companies generally give preference to a doctoral degree or masters in computer science or mathematics. It is a good step to do a master’s degree after B.Tech in AI.  A candidate has to have strong mathematical, analytical, and programming skills. He should also have expertise in deep learning, neural networks, cloud applications, and machine learning.

2. Business Intelligence Developer

Business Intelligence is also a highly demanding career option in AI. As this technology brings a revolutionary change in new industries, the demand for BI developers is rising rapidly.

This position’s primary goal is to analyze complicated data sets to find out market and business trends. The job responsibilities of these professionals involve enhancing the profitability and efficiency of a business. They work towards designing, maintaining, and modeling complicated data quickly and easily accessible cloud data platforms.

A candidate who wants to pursue this role should possess strong analytical and technical skills. They should communicate by displaying problem-solving skills. Unlike other job positions, a candidate only requires a graduation degree in this field.

The candidate must have a good level of experience in SQL queries, data mining, data warehouse design, SQL Server Reporting Services, BI technologies, and SQL Server Integration Services. A combination of certifications and on-the-job experience is desirable to get this job.

3. Data Scientist

Professionals employed in this position are responsible for collecting, analyzing, and interpreting large and complicated datasets. It leverages both predictive analytics and machine learning. They play an important role in building algos that are geared for the data collection for analysis. To be a data scientist, it is essential that a candidate has to be proficient with big data tools and platforms that include:

• Hadoop
• Hive
• Pig
• MapReduce
• Spark

In addition to it, a data scientist has to be highly experienced in programming languages, and statistical computing languages such as:

• Perl
• Scala
• Python
• SQL

Candidates who possess the below skillset are given more preference:

• Experience in machine learning
• An advanced degree in mathematics, computer science, and electrical engineering
• In-depth knowledge and good experience on the Hadoop platform and cloud tools.
• Ability to comprehend unstructured data
• Strong communication and analytical skills to flawlessly discuss their discoveries with business leaders.

4. Research Scientist

This is a leading career in AI that involves expertise in various AI disciplines, including deep learning, machine learning, applied mathematics, and computational statistics. Candidates need to show extensive experience and knowledge in graphical models, computer perception, natural language processing, and reinforcement learning.

To be a research scientist, it is essential to have a doctoral degree and an advanced master’s in computer science. A majority of hiring firms lookout for technology professionals who need a deep understanding of benchmarking, distributed computing, parallel computing, AI, and machine learning.

5. Big Data Architect or Engineer

This is one of the best jobs in AI. Architects and Big Data Engineers play an essential role in building an ecosystem that enables businesses to communicate with one another and collate data. Candidates who possess a Ph.D. in computer science and mathematics have an added advantage.

Big data architects and engineers are tasked with designing, planning, and building the big data environment on Spark and Hadoop systems. Candidates also need to show programming experience using Python, Java, C++, and Scala. They should possess in-depth experience in data visualization, data migration, and data mining.

How Much Can You Expect To Earn In Various Fields Of AI?

A candidate who possesses the desired qualification and competency in Artificial Intelligence can draw enormous salaries under different positions. Referring to the top job national and international job portals, we have computed the average salary earnings of an AI specialist for key positions such as

Machine Learning Engineer: an average salary of $114,855

Data Scientist: an average salary of $120,930

Business Intelligence Developer: an average salary of $92,178

Research Scientist: an average salary of $99,609

Big Data Architect/ Engineer: an average salary of $151,207

Who Are The Top Recruiters For AI Roles?

The need for AI professionals is for both the star-ups firms as well as tech giants like Microsoft. After performing research on reputed online job platforms, we have found a list of the leading employers who have been hiring AI professionals over the last few years:

• Microsoft
• IBM
• Facebook
• Intel
• Accenture
• Adobe
• Samsung
• Amazon
• Lenovo
• Uber
• NVIDIA
•  

As several new start-up firms are launched every year, so there could be an expansion in this list. Overall, we can see that a career in AI brings plenty of career opportunities under different positions.

What Are The Top Universities To Pursue A Degree In AI?

Employers value candidates who have passed from prime universities in the world. Following are the top universities that offer AI course in India:

1. IIT Hyderabad

It is one of the leading institutes to offer a full-fledged B.Tech. Program and M.Tech Program in AI. It is likely the third institute worldwide after Carnegie Mellon University, US and Massachusetts Institute of Technology, US.

Students who are pursuing B.Tech. In Mechanical Engineering or Chemical Engineering can do a minor in Artificial Intelligence. This ensures that students of IIT Hyderabad in all disciplines are well armed to meet the AI challenges that lie ahead.

The B.Tech course seeks admission into the program via the JEE-Advanced.

This program offers a holistic understanding to students that comprises algorithms from the Signal Processing from Electrical Engineering Department, Computer Science Department, Mathematical Foundations, and Robotics from the Mechanical Engineering Department. Moreover, the influence created by AI and associated technologies in fields such as bias, privacy, bias, and other similar issues will be a prime component of the B.Tech. Program.

All the students who enroll in this course will get a proper understanding of the basics of theory and practical elements of AI and Machine Learning. It will help fulfill the pressing requirements of the nation in these fields.

They provide in-depth training on several aspects of AI, ranging from ethical issues to machine learning algorithms. This well-rounded and comprehensive training on smart Artificial-Intelligence based technology solutions will make them highly sought after by the Industry.

Data science is another prominent technology that involves the collection of data for analysis. As the modern-age computer systems are based on binary data comprising of 0’s and 1’s, data science plays a pivotal role in developing binary algorithms. This technology is also beneficial in cloud storage (iCloud, one drive, etc.) that offers numerous advantages over traditional storage systems.

2. Benett University, Delhi NCR, India

It is one of the best B.Tech Colleges In India that offer the most focussed program in Data Science and other prominent technologies. The university has its own Microsoft established lab. It has academic tie-ups with the best of the league universities, including Florida International University, USA, Georgia Tech, Babson Global, Inc., USA, and The University of Nebraska at Omaha, USA.

Presently, this institute offers a Computer Science program with a specialization in six areas as Artificial Intelligence, Data Science, Blockchain, Cybersecurity, Gaming, and Virtual Reality, and Robotics and Automation. All these courses help students pursue their passion without weakening theirfundamentalbasics of Computer Science Engineering.

Benett University, Noida, is the Official Learning Institute of NVIDIA. Its faculty members are NVIDIA Ambassadors to offer various AI Technologies that include Computer Vision, Natural Language Processing, Video Analytics, etc. The university, in collaboration with NVIDIA, organizes several workshops and Hackathons.

Bennett University also offers 32 sophisticated and ultra-modern labs with leading corporates as Programming Lab and Information Management System Lab, CSE and Instruments labs- Apple iMAC lab, NVIDIA Super Computer Lab for Deep learning, Bennett-NVIDIA Center of Excellence for Artificial Intelligence, Dell EMC- Bennett Data Analytics Lab, etc.

They aim to offer extensive hands-on training to the students to build design, conduct experiments, gather, analyze, and interpret data and work independently in teams. This technology keeps students exposed to recent technology all the time.

3. PES University Bangalore

Established in 1972, PES university offers several Under Graduate and Post Graduate courses to students in Data Science. The subject is included as a mandatory subject in the third semester of B.Tech CSE students. They can opt for Big Data Science as an elective subject (HDFS, Spark, Streaming spark, Hadoop, HIVE, MLlib, EC, and Hbase).

The University offers facilities based on international standards. It also provides the right blend of contemporary education and industrial exposure to the students. The programs offered by the Computer Science department are designed to create an internationally skilled workforce for the ICT (information and communication technology) industry.

Their B.Tech program aims at providing comprehensive training to students to build strong theoretical foundations. Students work with revolutionary computing technologies, complex engineering problems, and design solutions to prepare them for the industrial environment.

About Data Science

Due to the increasing use of the internet, companies can access vast amounts of structured, semi-structured, and unstructured data and scie, or data-driven science, which uses statistics, computer science, and mathematics to study and examine data.

The key to Science is to identify valuable information to study deciexamianalyzeze trendspredict and manufacture aoduct. The aim is to manage the collection of digital data in a business successfully.

The major three data science components are an organization, packaging, and delivery of data. It is the blend of data implication, development of algorithms, and implementing technology to solve complicated difficulties in an analytical way.

Scope Of Data Science

A person who specializes in data science is called a data scientist. He helps organizations by performing research and data analysis to predict trends, business insights, and growth based on huge data.

They use the knowledge of programming, mathematics, and statistics to organize the data. As the amount of data produced by the businesses increases, data scientists’ demand also increases in the organization. Data scientists help convert huge stacks of raw data into meaningful business information and determine applicable designs and patterns.

This information helps identify the future objectives of a business. Data science professionals are increasingly employed in trades, non-profit organizations, and public agencies.

Why Are Data Science Professionals In High Demand In Companies?

Data Science is an indispensable need for organizations worldwide. The right use of enormous raw data can significantly help better handle data and deliver solutions to problems.

Here we have outlined a few reasons that show why data science is an important part of the global economy.

• Data Science helps companies to identify their target customers and connect with them effectively. It helps them form a deep and improved understanding of how their customers will use their products. This information helps an organization in improving the quality of its products.
• Data Science enables companies to express their story in an engaging and impactful way. This helps in the creation of improved product connections.
• The Data Science strategy can be applied to in various industries such as healthcare, education, and travel. It helps industries identify their challenges and address them in the best way possible.
• Using advanced tools, companies can utilize big data to resolve complicated IT issues and manage resources efficiently and successfully.
• Data science is becoming popular as it helps in the sound functioning and growth of a product to realize product goals. This, in turn, leads to greater revenue generation and expansion in the customer base.

What Are The Future Prospects Of Data Science?

Data science is an expanding field that is becoming an integral part of almost all sectors. Data science helps the healthcare industry by providing them new solutions to take efficient care of patients. Its positive impact in the field of education is visible. Data science offers better opportunities for students to help them widen their knowledge.

Thus, data science aims at offering the best-level of solutions to create a sustainable future. To execute this goal, an organization must have adequate systems and resources to achieve their goal.

Based on the present market study, it has been identified that there is a shortage of skilled data science professionals. This has posed a challenge to businesses, companies, and organizations worldwide. Whether it is the retail industry, education, or healthcare, there are estimations that data science ‘ demand professionals’ demand will rise enormously shortly.

How To Make A Career In Data Science?

Looking at data science’s potential, this field offers plenty of lucrative job prospects to skilled professionals.  The right way to pursue a career in data science is by doing Bachelors of Engineering/ Bachelors of Science/ Bachelors of Technology (B. Tech)/ Bachelors of Commerce/Bachelors of Economics. It is important to take Computer Science/ Mathematics/ Physics/Econometrics/ Statistics/Business/ and Economics as the key subjects.

For securing high-level job positions in data science, candidates need to get good knowledge about programming and database languages such as Perl, SQL, R/SAS, and Python. They should also know to interact with different kinds of systems that include MongoDB, Cassandra, the Hadoop Base, CouchDB, etc. With these qualifications, you are all set to make a successful career in data science.

What Are The Available Career Options In Data Science?

Data Science is one of those fields in the job market that is gaining extraordinary traction. This is because technologies such as data mining, machine learning, data analytics, Big Data are becoming more applicable to the conventional IT industry. Organizations all over the world are fiercely fighting to recruit skilled data professionals. Due to this, the financial packages for varying data science roles are increasing at a steady rate. Here we have listed a few lucrative job options for aspiring data science professionals.

1. Data Scientists:

Job Responsibilities:

• They are the data specialists who use mathematical and statistical models to perform adjustments to the data.
• The data scientist applies his theoretical knowledge of algorithms and statistics to determine the best method to solve any data science problem.
• They carry out extensive research and figure out the business implications of data.
• Other responsibilities of a data scientist Predictive Modeling, Reporting and Analysis., Distributed Computing, and Data Visualization.

Qualifications Required:

To become a data scientist, you need to start off by earning graduation in IT, mathematics, physics, computer science, or other associated fields.

• The candidate must have a good knowledge of programming languages such as R, Python, SAS, Hive, SQL, Spark, etc.
• He should also have expertise in the areas of statistical modeling and distributed computing.
• The knowledge of database architecture, data modeling, data analysis process management, reporting tools, and data mining is essential.
• He should have a research-oriented mindset with good command over statistics and mathematics.

Salary Prospects:

Data Scientist is the highest paying position in the field of data science. Below is the current salary trend for a data scientist at varying stages of their career.

0 to 5 Years: $89,000 per annum

5 to 10 Years: $109,000 per annum

10 to 20 Years: $121,000 per annum

Over 20 Years: $148,000 per annum

Average Salary: $91,588 per annum

2. Data Engineers:

Job Responsibilities:

• A data engineer plays an integral role in any data science project. They are involved in the design, creation, execution, and upkeep of scalable data management systems.
• They help build high-performance algorithms, conceptual models, and prototypes based on the blueprint provided by data architects.
• Their prime responsibility is to provide clean, verified, and usable data to data analysts to carry out a detailed analysis of data.
• They possess sound knowledge in software engineering that helps them deal with huge piles of data. They have expert knowledge of computer science that helps in processing large datasets.
• Their forte lies in coding. They are well-versed in various programming languages such as Java, Python, etc. They take the predictive model and data sets from the data scientist and implements the code on it.

Qualifications Required:

To get an entry-level job as a data engineer, a candidate should possess graduation in computer science, applied mathematics, physics, software engineering, statistics, or any associated field.

• They should possess good knowledge of data storage, warehousing solutions such as NoSQL and SQL.
• They should also be well-versed with programming frameworks that include Spark and Hadoopwhich help source data and process it.

Salary Prospects:

Data Engineers is one of the most sought professions that pay a high salary to professionals based on their expertise and experience.

0 to 5 Years: $84,000 per annum

5 to 10 Years: $112,000 per annum

10 to 20 Years: $117,000 per annum

Over 20 Years: $102,000 per annum

Average Salary: $89,111 per annum

3. Data Analysts:

Job Responsibilities:

• A data analyst’s job is to evaluate the data to provide reports that show valuable insights about the data.
• They present these meaningful insights(text and numerical data) in the form of presentations, graphs, dashboards, and charts to help the organization understand problems and arrive at solutions.
• Based on the extracted data, they help identify trends and the creation of predictive models.

Qualifications Required:

Any candidate who aspires to become a data analyst should secure a bachelor’s degree in mathematics, marketing, economics, statistics, computer science, or finance.

• They should be thorough in machine learning and various programming languages that include Python, R, etc.
• They should also have sound knowledge of spreadsheets and database systems.
• Knowledge of statistical models, mathematical procedures, and algorithms is also beneficial.
• They should possess sound analytical skills.
• They should have expertise in working with several business intelligence methods, reporting tools, and data visualization procedures.

Salary Prospects:

Data analysts earn handsome paychecks that increase with their experience. The salary trend for a data analyst based on their experience level is mentioned below as:

0 to 5 Years: $53,000 per annum

5 to 10 Years: $63,000 per annum

10 to 20 Years: $64,000 per annum

Over 20 Years: $66,000 per annum

Average Salary: $56,634 per annum

4. Statistician:

Job Responsibilities:

• The role of a statistician is to gather, examine, and interpret measurable data using statistical theories.
• They should be well versed in implementing statistical methods and approaches to data.
• They should determine data collection methods and the type of data required for answering specific types of questions.
• They should have a logical mindset and a strong working background in statistical practices and procedures.

Qualifications Required:

For an entry-level data statistician, it is required to earn graduation in computer science, i.e., B.Tech with subjects like data science, mathematics, survey methodology, statistics, etc. For higher-level job positions, a candidate needs to have a master’s degree.

A statistician should possess the following skills:

• Proper background in statistical methodologies and theories.
• Knowledge related to distributed systems such as MapReduce and Hadoop.
• Expertise in machine learning and data mining.

Salary Prospects:

The salary of a data statisticians falls between data analysts and data engineers. The salary trend for statisticians for the entire career term is mentioned below:

0 to 5 Years: $66,000 per annum

5 to 10 Years: $80,000 per annum

10 to 20 Years: $96,000 per annum

Over 20 Years: $105,000 per annum

Average Salary: $70,435 per annum

5. Database Administrator:

Job Responsibilities:

• The main responsibility of a database administrator is to ensure that the organizational system’s various functions are working effectively.
• They also make sure that the database should be easily accessible to authorized individuals in an organization.
• It should also be handled all the time safely. A DBA uses specific software for storing as well as organizing data.
• Their main responsibility involves ensuring the security, integrity, and performance of a database system.
• Their other duties include capacity planning, data restore and backup solution, security configuration, database design, troubleshooting, and performance evaluation.

Qualifications Required:

To become a DBA professional, a candidate must secure at least graduation in computer science or any associated field. In addition to it, the candidate should possess the following requisite skills:

• In-depth knowledge of DMS or database management systems.
• Good knowledge in data design and data modeling.
• Good practical experience in performance optimization and security hardening.
• Proficiency in troubleshooting and solving potential issues.
• Proficiency in recovery and backup methods.

Salary prospects

Numerous domains in the IT field need qualified DBA in high numbers. The salary of a Database Administrator depends on his experience and skill-set. Based on the latest salary trends, a DBA can expect to earn in the following range.  

0 to 5 Years: $60,000 per annum

5 to 10 Years: $78,000 per annum

10 to 20 Years: $89,000 per annum

Over 20 Years: $87,000 per annum

Average Salary: $70,613 per annum

6. Data Architect:

Job Responsibilities:

• These professionals create data architecture to identify and process the raw data as per the organizational requirements.
• They have to integrate, centralize, protect, and maintain the data source from several data management technologies and systems to create a data science project proposal.
• A data architect should ensure that the data environment remains secure, stable, and available.

Qualifications Required:

Candidates should have a graduation degree in computer science, information technology, computer engineering, or an associated field. He should know the following technologies such as:

• Good understanding of data-driven programming languages such as SQL, XML, Hive, Spark, etc.
• Practical proficiency in ETL, Business Intelligence tools, spreadsheets, data mining, and data warehousing solutions.
• In-depth knowledge of DBA(database architecture).

Salary Prospects:

The salary of a data architect is based on his proficiency and experience level. This is what a data architect can expect to earn in his career based on the present salary trend.

0 to 5 Years: $85,000 per annum

5 to 10 Years: $108,000 per annum

10 to 20 Years: $128,000 per annum

Over 20 Years: $133,000 per annum

Average Salary: $111,475 per annum