What is the future of Data Science & Artificial Intelligence?

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The Sway Towards Data Science & Artificial Intelligence

Today is the age of the digital era. We do everything from buying and selling to working and entertainment online. In fact, the world today depends on digital data. Hence the use of Data Science and AI has increased at a rapid pace. A computer is used to do work on its own like humans. Machine learning is an application. Programmers use it to develop a computer system. In fact, data science, AI, and machine learning are all interrelated. Most companies are making use of these to achieve their targets. Moreover, a company uses lesser time and fewer resources. There is a sea change in various sectors of society due to the use of artificial intelligence and machine learning. In fact, many organizations are investing in these sectors to reap the benefits of efficiency at a low cost. 

Scope of Data Science

It is the fastest-evolving field globally. Data Science applies machine learning to analyze future estimates. Data Scientists research large data using techniques and AI to understand trends and patterns. In fact, this information helps companies to thrive in this competitive world. In addition, it helps them not only to make changes but also to take decisions. Data Science is used in cyber fraud detection, weather prediction, the Healthcare sector, outbreak of pandemics, etc. Since this can be used in diverse fields it has emerged as the go-to career. In fact, it is considered one of the most stable jobs not only in India but also in the world. Having said that, a data scientist needs to keep updating his skills. Earlier the focus was more on the statistical handling of data but slowly it is moving towards coding and machine learning.

Scope of Artificial Intelligence

Artificial intelligence forms the base of computer learning. Computers use AI to analyze vast amounts of data and use them to make decisions. In addition, it also helps create new innovations in the field using lesser time than humans. We have already witnessed the application of AI in smartwatches, cars, the health sector, banking, finance, and marketing. It has touched almost every industry.  Furthermore, AI and machine learning are going to take scientific research to greater heights. In the years to come, AI will be used for health diagnosis without any clinical trials. It is going to impact not only the economy but every sector of society. Using machine learning AI has made a significant number of innovations. In fact, the field of AI is forecasted to show a growth rate of 13.7%. All in all, this trend shows an upward curve.

A Precursor to A Career in Data Science And Artificial Intelligence

There is a growing need not only for data scientists but also for professionals trained in Machine Learning and Artificial Intelligence. If you have set your goals on a career in Data Science or AI then these are the things that need to be considered

• Bachelor’s or Master’s degree in data science, machine learning, or AI
• Certification courses to update skills.
• Upscale skills like management of database, basics of coding, communication, and effective business management skills.
• Make use of internship opportunities provided by training institutes.
• Soft skill development.
• The learning journey in Data Science never stops. It keeps evolving with time.
• Actively participate in the discussion of case studies during certification courses.
• Along with theoretical knowledge, practical know-how is beneficial.
• A general awareness of the changing trends in the field of Data Science and AI.
• Certification courses in Machine Learning.
• Basics of Programming and Web Development knowledge.

Henry Harvin

India Today has ranked Henry Harvin as No. 1 among the top training courses for Data Science. The institute has provided training to nearly 3 lakh students. The certification they provide is affiliated with the Government of India. Their course is a perfect blend of theory and practical knowledge. It equips aspirants with the right skills required in the field of Data Science.

Data Science Course Details

• Duration: 32 hours of online classes. Access to 50 hours of e-learning sessions.
• Trainers: Industry experts with more than a decade of experience.
• Curriculum: Updated content with a perfect blend of theory and practical experience. Knowledge of Python.
• Internship: After the course completion.
• Job guarantee: 100% placement assistance.
• Membership: Free 1-year membership of Henry Harvin Academy.
• Live projects: Case studies help students to gain practical knowledge.
• 100% money-back guarantee if dissatisfied with the course.

Artificial Intelligence Course 

PC Quest has ranked Henry Harvin”s AI Course as No.1 among other upskilling courses.

• Course Content: Well formulated to meet market needs. Fundamentals of Machine learning and AI.
• Practical training: 100% practical training provided.
• Free e-learning: Free access to e-learning materials.
• Placement: They provide not only job assistance but also internship after the course.
• Master class: 52 sessions.
• Soft skills: They provide interview training.
• Practical training: Case studies give hands-on training along with theory classes.
• Certification: It provides certification after the course.
• Trainers: Experts in the field with more than 10 years of experience.

Machine Learning Course

BestCourseNews.com has ranked Henry Harvin’s Machine Learning Course at No.3 among other top course providers.

• Content: Focus given on hands-on training.
• Duration: 32 hours of live, online sessions.
• Certification: The Government of India recognizes its certification.
• Hackathons: Free access is given.
• Job support and internship: Provided after the course.
• Free access: They provide free access to E-learning materials.
• Trainers: Not only are they experts but they also have more than 15 years of experience.
• Master class: It provides free master class sessions.

Perks of The Application of Data Science and AI

• The use of machines has replaced a chunk of the manpower. However, this manpower can be used for other functions.
• Not only production but also efficiency in various sectors has increased manifold
• Brings about technological innovations to not only meet but also measure customer expectations.
• Not only predicting future disasters but also preparing to face them effectively.
• Reduced percentage of errors.
• The use of AI and Machine Learning in Data sciences helps not only to analyze data but also to use it to take important business decisions.
• Helps increase sales and profits. Data Sciences study and tap the customer journey which makes marketing easier. 
• They help in curbing fraud. It puts fraud prevention systems in place.
• Easier recruitment methods. Data Science helps screen thousands of resumes at one go. They use different analytical techniques to choose the right candidate. This not only saves time but also saves effort.

Co-relation Between AI And Machine Learning

These two come under the field of computer science. They are the most popular technologies used in the creation of intelligent applications. Though they may appear similar they are both altogether different in their functions and usage. 

Points of Differences

Artificial Intelligence

AI is a subject in computer science. It creates systems that can think and behave like human beings. Artificial intelligence, the word denotes a man-made system with thinking abilities. Moreover, AI need not be programmed to give the required outputs. In fact, they are created in such a way that they use their own intelligence to work and give the desired results. AI uses machine learning and other algorithms to function. AI is divided into three groups: weak, strong, and general. They can be used for multiple domains.

Machine Learning

Whereas Machine Learning is used to collect knowledge from a given data. Hence, it is a subset of AI. Moreover, Machine Learning enables systems to gain knowledge based on past data. Just like AI, they are not pre-programmed. In addition, machine learning not only helps predict future trends but also helps take decisions. They analyze past data to forecast the future actions to be taken. It uses vast amounts of data in order to give perfect results. They are perfect exclusively for one particular domain. It can be classified as Supervised, Unsupervised, and Reinforcement learning.

Is Data Science A Good Career Option?

With the increase in the use of technology, huge amounts of structured and semi-structured data are easily available. Hence the demand for data scientists is on the rise. Moreover, the work of data scientists involves understanding, analyzing, and interpreting data. In fact, this is the requirement of most companies, both public limited and private. So, the future of a data scientist looks bright and positive. As data increases more data scientists will be required to handle the data. In addition, the job is lucrative and challenging. There is scope for further learning while on the job. However, it does not stop here. One needs to keep upskilling and updating in order to keep up with the changing market trends. Though there is a great demand for data science professionals there is a huge gap between demand and supply. Hence, Data Science is a great career option.

Skills Required to Be A Data Scientist

• Analyzing abilities
• Effective communication
• Planning
• Co-ordination
• Time management
• General awareness of the market
• Researching skills
• Designing and Implementation
• Visualization of data
• Handling and Managing tools

Knowledge Requirements

• Maths
• Algorithm
• Statistics
• Machine Learning tools
• AI tools and techniques
• Programming
• Tools for Data Visualizations.

Is Machine Learning A Subset of Artificial Intelligence?

The method of using mathematical tools and techniques to assist computers to understand and learn without giving any direct orders is called Machine Learning. Since it is one of the applications used in AI, it is a subset of AI. It is one of the latest modern innovations. In fact, it has improved many business and manufacturing processes as well as different sectors of society. Thereby, improving the standard of living of people. Data analysis requires the use of many algorithms. Machine Learning can bring about accuracy while forecasting future market trends. A computer uses AI not only to think but also to take decisions on its own like humans. Whereas machine learning deals with how a computer develops its intelligence. In fact, it uses past data to analyze and predict the future output.  Since it is a part of AI it is rightly a subset of AI.

Real-Life Applications of Data Science and Artificial Intelligence

1. Education

• Creating course content, textbook guides, and video content.
• Customizing content based on the needs of the students.
• Students get extra learning material even without the assistance of teachers.
• Regular monitoring of the progress of students. Moreover, they conduct tests and revisions at regular intervals.
• It facilitates not only the correction of test papers but also assigning marks. 
• Helps send messages to students. In addition, it helps improve parent-teacher interaction.

2. Online Shopping

• It facilitates better engagement with customers by giving recommendations.
• Improves customer relations and helps maintain customer loyalty.
• Shopping online becomes easier with the help of virtual assistants and chatbots.
• In fact, AI can help prevent fraud while making payments for purchases through cards.
• It helps to not only organize but also analyze customer reviews.

3. Daily Life Applications of AI

• Companies like Tesla use AI to train computers to think and act like humans to drive and to help detect obstructions while driving. Hence, this helps to prevent accidents.
• AI filters in email help to trash and filters unwanted messages.
• Our phones and computers use facial recognition for identification. It is an application of AI. In addition to identification business houses also use it for security reasons.
• Social media platforms use AI to generate recommendations. In addition, this increases user engagement. 
• GPS helps gauge not only traffic but also aids by giving accurate directions to our destination.

4. Human Resources

• The HR department uses the applications of data science to screen candidates for the hiring process.
• In addition, AI assesses applications based on certain parameters.
• In fact, the screening process becomes not only simpler but also less time-consuming, and cheaper.

5. Healthcare Sector

• Data Science and AI applications have helped build modern machines to not only detect but also treat cancer cells.
• It helps assess lab and other medical reports to help make an early diagnosis.
• In fact, AI uses past data to discover new medicines for diseases.

6. Robotics

• Helps to carry heavy goods not only in factories but also in hospitals, and storehouses.
• Cleaning machines, equipment, and offices.
• Managing inventory in a business.

7. Social Media

• AI uses likes and the accounts one follows to analyze information. Then such posts appear on Instagram.
• On Facebook, AI translates posts from different languages on its own.
• On Twitter, users use AI to detect fraud and delete undesirable content. In fact, AI gives recommendations based on the data available.

8. In The Field of Agriculture

• Data Science and AI help to pinpoint defects in the soil.
• AI helps to detect the growth of weeds.
• Moreover, with the help of data science, farmers can reap good crops at a faster pace.

9. Marketing

• Marketers can design advertisements based on market analysis.
• AI helps create content based on the volume of consumers.
• In fact, the marketing departments develop campaigns based on the consumer data available.

10. Finance and Commerce

• AI is used in retail as well as personal finance.
• It passes on information to users regarding the various services provided by the bank.
• AI helps not only to detect but also to stop fraudulent transactions.
• In addition, they help to assess loan requirements and the risks involved in it.

Conclusion

All in all, the future of Data Science seems bright. As companies realize the importance of data these fields will be in high demand. Data Science will bring about a huge improvement not only in the production of goods but also in providing services. In fact, there is a huge demand for professionals with certification in Data Science, AI, and Machine Learning. Since many new start-ups are coming up the number of job requirements is going to double. These are great fields to implore and learn. Skills in Data Science, AI, and Machine Learning will set a candidate apart from the rest. Moreover, this is one field that will never become obsolete. If you dream of a lucrative and stable career with a good pay packet then these are the fields to invest in. Hoping that your dreams of a career in Data Science and AI come true.

Recommended Reads

• Data Science VS Business Analytics [2022 Updated]

• A Comprehensive Guide on How to Become an AI Designer

• Data Science vs. Artificial Intelligence-Key Differences

• How Is Data Engineering Different From Data Science?

• Data Science Jobs in India in 2022 [Updated]
• Data Profiling, Process and its Tools

FAQ’s

Q1. Is Data Science a wise choice to make?

Ans. Yes, with more and more companies relying on data to make important business decisions, it is indeed a wise decision to invest in a Data Science course.

Q2. Is Machine Learning a part of AI?

Ans. Yes, it is a subset of AI. It is an application used in AI.

Q3. Which is the best option Machine Learning, Data Science or AI?

Ans. All three fields are interrelated. Hence it is best to hone skills in all three fields.

Q4. How important is it to upskill after I finish the courses?

Ans. The field of Data Science, AI, and ML are evolving. Hence it is very important to keep updating and upskilling to learn and hone skills from time to time.

Q5. Does a Data Scientist have more opportunities to choose from?

Ans. Data Science is used in almost all sectors of manufacturing as well as service-oriented businesses. So, there are manifold roles one can choose from. The opportunities are indeed diverse.

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