Why is Data Science a Good Career in 2021?

Being a data scientist is only growing in demand over 2021 and is showing no signs of slowing down. It is estimated that around 11.5 million jobs in data science will be created by 2026 in the US. But, why is that the case? This article seeks to answer that very question.

  1. Use in Companies

Due to the ever-growing base of Big Data, every company is looking to utilize all available information to have a massive competitive edge.

Data Science CareerA data science career under a company is a frontier-field that finds new ways to better one’s products and services after utilizing past stores of information and/or case studies.

This work hence involves finding various avenues of data and finding new ways of processing and drawing conclusions from that data.

  1. Use in Studies

Being a form of study that is still in its nascent stages, a data science career may not be motivated by finding profit for a certain industry but also increasing the ambit of human knowledge. One might also work on designing a data science course from others to learn from.

  1. Proper Pathway

While being a data scientist requires a lot of work, the exact path to such a goal has been charted time and time again. There is a great degree of resources available now to become proficient in various aspects related to the data sciences. Other than doing a basic data science course, one may partake in learning various related fields like programming and big data processing from various online platforms (e.g. Imarticus learning).

  1. Demand Doesn’t Slack

The demands for data sciences have also increased due to the new atmosphere generated by Covid-19 and the near-worldwide lockdown because of it.

Data Science Roles

It has been studied that 50% of the data science organization showed no slow-down and have seen growth. This requires one to find new ways to collect data, as well as use that data to aid in multiple projects. These may involve helping set up new modes of businesses, and helping older businesses change their plans to suit their new circumstances. Furthermore, it may aid in improving a range of services on a global level.

  1. Diverse Skillsets

It is easy to switch into being a data scientist incorporating your present skillset. Whatever your present occupations and/or interests may be, it can lend an avenue to collecting data on that specific domain.

Data Science TrainingThey can complement these skills with learning standard data sciences’ skills. Former data analysts may also expand on their present sphere of knowledge to become data scientists, with relative ease.

  1. An Expanding Field

In 2021, a lot of past data science models are up to open-source scrutiny. Hence, even in this new field of human knowledge, one can have a sizable understanding of multiple avenues of collecting and processing data. Their entry into data sciences will work to expand on this field of knowledge.

In conclusion, one can see that it is indeed highly fruitful to be a data science in this present day and age. One can channel his/her present skillset into this occupation as well and aid a burgeoning field of human growth and knowledge.

What is the difference between Business Analyst and Product Analyst Roles?

What is Business Analyst: 

A business analyst is an individual who analyses an association or business area and records its business, cycles, or frameworks, and evaluates the plan of action or it’s joining with innovation. He helps in managing organizations in improving their cycles, items, administrations, and programming through information investigation.

They are also a link between Information Technology and business using data analytics. Business analyst courses are booming with many students opting for a career in this field. Universities like Berkley and Cornell are offering business analyst courses.

best big data analytics course

A business analyst helps a company to boost its business by improving the functioning of the company, the products, and software using data analysis. This role of a business analyst not only demands technical skills but also requires experience that enables an individual to analyze people and situations.

A product analyst on the other hand observes the current trends in the market, the demands, and expectations of the consumer and then guides businesses to develop the right marketing strategies for the products. They compare the products of the company with the trends in the market to make a product suitable as well as profitable.

A business analyst and a product analyst work together to ensure a company’s profit and business but they have different responsibilities. Many product analysts usually start their careers as business analysts and transition later. They both work closely.

A product manager takes full control over a product. They own the product in every right and are also responsible for its future in the market. They work on the marketing strategies for the product and analyze its performance in the market while chalking out the profit and loss based on market research. They work closely with the sales team to ensure that it reaches maximum consumers.

A business analyst enables change in the company according to the needs and provides solutions. They bridge the gap between IT and business teams. If the business team desires a change in the software system, the analyst steps in and facilitates the discussion and ensures the necessary software solutions are provided. A business analyst collaborates and makes sure that requirements on both sides are met and how the updated business will be.

If we had to consider the biggest difference between a product analyst and a business analyst, it is that the former has more decision-making power.

  • They collaborate with executive teams to ensure maximum marketing for the product.
  • They decide the software’s function.
  • They have financial responsibilities towards the company and the product.

A business analyst is like a catalyst. They are responsible for changes in the organization. They identify the problem and tackle it by providing solutions. If it’s about software changes, the analyst works together with other departments in the organization as well.

It’s the business analyst suggesting the changes and the technical team delivering it them. A business analyst ensures that everyone agrees to the changes and they are also responsible for updating everyone about the upgrades in the business process.

A product analyst focuses more on the interests of the consumers and market trends. The product is their responsibility. They tend to work on how the product will benefit the market and the consumers. Throughout the project, the product analyst questions ‘why’ to determine the best solutions for the users.

One of the most essential responsibilities of the product analyst is to manage the backlog of the product to increase its end value. The backlog helps the team to concentrate on the internal work and other important aspects. After the backlog is created, it’s important to maintain the backlog to ensure prioritization. They also oversee every stage of development of the product including the planning, processing, and reviewing.

For an organization to function properly, the collaboration between a business analyst and product analyst provides the best way out of every problem, be it technical or practical. To tackle such situations, business acumen, as well as technical expertise is important.

A Complete Guide: Format For The Engineering Project Report!

An activities show the amount you have realized, what are your abilities, how you tackle issues.

While a task report show how efficient you are, what is the profundity of your insight, how well would you be able to clarify stuff.

Venture reports are vital for scholarly just as self evaluation.

The extent of a designing task stretches out past the educational program and significantly helps one in finding in their future center work or getting higher investigations affirmation in presumed colleges.

By and large, designing activities are viewed as the impression of an understudy’s learning in his/her designing. In any case, doing a decent undertaking alone isn’t sufficient, it should be introduced flawlessly in the standard configuration so it can address the various parts of the venture in an illustrative way.

A portion of the critical highlights of drafting great ventures report are:

Works with faster and simpler approach to convey the data

Can aid specific perusing

Simpler route to substance with numbered headings and sub headings

Better clarifications with figures, tables and diagrams

Here are 4 hints for your venture report

1. Masterminding the substance: The pages ought to be organized in a spin-off way to suit the various leveled principles. The accompanying configuration is prescribed to orchestrate the substance of the undertaking report,

Cover sheet

Endorsement record or Certificate

Theoretical

Affirmation

Chapter by chapter guide

Rundown of Tables

Rundown of Figures

Rundown of Symbols, Abbreviations, Nomenclature utilized

Sections included

Trials and Results

Ends and Recommendations

Addendums

References

2. Page measurements and restricting particulars: The standard page measurement to present the report is A4 and winding restricting is liked to tie the report (as it works with simpler evacuation and reworking of papers)

3. Readiness design:

Inclusion and page title: This is the beginning page of your undertaking report and every one of the letters of your venture title ought to be promoted and the page ought to be bereft of page numbers. The undertaking title ought to be trailed by the association name to which you are presenting the report and the understudy’s subtleties (name, reg number, assignment) toward the finish of the page. Likewise remember your school logo for the top corner.

Bonafide testament: If you have done your venture under an association or straightforwardly in an industry, you need to give the bonafide endorsement to confirmation. Follow a similar organization (A4) and get it bore witness to with the concerned authority prior to encasing in the report.

Presentation by creator: The revelation is an explanation that ought to be given by the understudy that he/she has finished the undertaking all alone without any contentions. It should bear the mark of the understudy toward the end and furthermore ought to be supported by the venture guide.

Unique: This page addresses the synopsis of the venture. So outfit the subtleties in an exact and productive way including the goal and point of the undertaking, strategies utilized, extent of the venture and task test examination (2-3 lines). The theoretical ought not be in excess of 350 words. It ought to have twofold line dispersing with Times New Roman text style and text dimension 14.

List of chapters: This page addresses the whole last year project report more or less. It ought to contain the subtleties of the principal, second and third level headers remembered for the report with their page numbers, to give simpler admittance to the peruser. The subtleties ought to be outfitted with one and a half dividing with lower case Times New Roman text style.

Rundown of images, contractions and classification: This will likewise be in the even arrangement where you need to clarify about the various images, truncations and terminologies that you have utilized in the venture report. This is critical as the perusers by and large allude to this page at whatever point they go over a term which is obscure to them. For this likewise you need to utilize one and a half dispersing and you should utilize just standard images, truncations and so forth

Page numbering: The fundamental parts are numbered in roman numerals (I, ii, and so on) Also, for the parts the page numbers ought to be in Arabic numerals (1,2,3 and so forth) at the base community.

4. Sections to include:

Presentation: The presentation page ought to give a concise data about the task’s point, level headed and future extent of the undertaking. It ought not contain any drawings or charts or figures.

Approach utilized: This part helps in assessing the philosophy used to execute the undertaking against the other standard procedures.

There are two sections in this:

1. Determination of Approach: The technique that rung a bell while considering tackling the issue. The strategy ought to be monetarily feasible and clarifying the technique in a reasonable methodology is significant.

2. Use of Selected Approach: how could you carried out the technique and which segments did you pick and what was the yield of picked parts and how could you settle the issue with the picked segments and clarify the segments independently.

Results and conversation: These parts ought to depict the data about the undertaking inside and out. It ought to likewise give all the hypothetical data about every one of the trials did. The subtleties of the task, for example, the circuit plan, reenactment results, measurable investigation, computations and results acquired ought to be clarified in a nutshell with slick figures, exhibit outlines, stream diagrams, charts, test pictures, portrayal photographs and so on

End and suggestions: This part sums up the entire undertaking featuring the learnings and significance of the venture. The suggestions ought to be identified with the subtleties given in the end. For the most part the end gave in regards to the task can be additionally adjusted and updated by alluding the proposals area which ought to disclose how to conquer the limitations of the undertaking.

Reference sections: Appendices are given to give advantageous data about the undertaking. Giving these in the above sections will make the venture report protracted. Addendums ought to be numbered utilizing Arabic numerals (Appendix 1, Appendix 2 and so forth) Every one of the reference sections ought to have the title of the suitable work made and ought to be addressed in the part’s page with similar titles.

Rundown of references: The posting of the references ought to be composed 4 spaces beneath the heading “REFERENCES” in sequential request of the main creator with single separating. Likewise the name of the creator/creators ought to be promptly trailed by the distributing year.

The Job Roles of IoT Specialists And Analysts Will See A Surge In The Near Future

The Internet of Things, also known as IoT, refers to the technology that allows different devices to connect and interact with each other virtually. Recently, IoT technology has become highly popular. The Bluetooth speaker you listen to music on or your smartwatch that connects with your smartphone are all examples of IoT at work.

From smart homes to industrial applications, IoT has many uses in our daily lives. That’s why the demand for IoT specialists is increasing rapidly.

Demand for IoT specialists is on the rise

India’s first semi high-speed train, the Vande Bharat Express utilizes an IoT-based system for mitigating collisions and thus, avoiding accidents. Its IoT system allows it to avoid accidents caused by equipment or human error.

Another similar user of IoT in India is Tea Tantrum, a tea supplier company. It uses IoT to check the moisture and ingredient ratios in its products. These are some of the many examples of how India is using IoT technology.

India’s IoT market is expected to reach $15 billion by 2020, making up for around 5% of the total global market. Currently, there are around 120 companies in the Indian market that offer IoT products or services. This number is also expected to rise as the number of IoT start-ups will increase in India.

Data AnalystWhat does all of it suggest?

It suggests that IoT career opportunities in India are on the rise. As the number of organizations that utilize IoT technology increases, the demand for IoT specialists will increase accordingly. Companies want experts who can identify their unique business problems and formulate IoT solutions that match their requirements.

How to capitalize on IoT career opportunities

As the demand for IoT experts is rising at a rapid pace, now would be the perfect time to pursue a career in this field. So, you might wonder, “How do I pursue a career in IoT?”

It’s quite easy. You should look for data science courses. Taking a data science course in India will help you learn the necessary concepts for becoming a professional in this field. Reputable data science courses teach you job-relevant skills such as Tableau, PowerBI, Python, Hadoop, Python, and R.

Learning these skills is vital as they help you keep up with the industry’s demands and stay on track. If you want to start your career early, then you can join a data science course with placement assurance. A data science course with placement assurance will get you a job right after you complete the program. You can kick-start your IoT career right away.

Another huge advantage of such courses is they offer you industry-endorsed curriculums and experiential learning (bootcamps, projects, and much more), allowing you to learn quickly and efficiently.

Conclusion

Online classesThe demand for IoT professionals is rising constantly. You can capitalize on this opportunity by taking relevant courses and becoming a certified professional in this sector.

To become an IoT professional, we recommend taking a data science course in India. If you’re interested in pursuing a career in this field, then check out our data science course.

 

Related Articles:

All You Need To Know About Python And Being A Certified Professional!

All You Need To Know About Hadoop!

Engineering Applications of Artificial Intelligence

Artificial Intelligence (AI) is now a commonly heard phrase. It has certainly captured the imagination of people owing to use of robots in movies and popular characters like Optimus Prime in The Transformers. AI is a combination of various branches of knowledge, intuition and skill-sets. The harder aspect is giving it the decision making and moral compass of humans. But we are inching closer.

AI is now being interwoven as an intricate part of standard machinery in various fields and has far-reaching industrial application than one can imagine.
The common fear is that AI will take over human jobs but in reality, it will dispose of the extra time spent in organizing and “hygiene” aspects of a job, like maintaining logs, cleaning workspaces, repetitive tasks which can be coded easily. It will leave humans more time and brain time to think over more complex aspects of engineering and design.
Also Read : How is Artificial Intelligence Transforming Healthcare
artificial intelligence
AI has become the new input in every aspect of daily things. Let us take a few examples.

Consumer Side

Take the engineering of a smartphone which uses voice commands to function and operate. Products like Amazon Echo, Google Mini and many other voices operated devices and apps are becoming the rage. There are products like Philip Hue which can work on voice and mood sensors to change the lighting.

Selling & Marketing

Use of AI chatbots is another new aspect. Chatbots are becoming the newest inclusion in website technology to increase the range of customer interactions. There are new companies which can enhance the customer’s interactive experience with the company personnel by giving a cue to the service representative on the tone and mood of the client along with previous experiences and their reactions then. This will give a holistic idea to the representative on how to approach and handle the client.

Automotive Intelligence used in Medical

Iprova, a Swiss technology company has come up with AI-based inputs as a means to their R&D. Instead of hiring specialist in each field for solving a problem, it has devised AI as a means to combined intelligence to pick up data points in an activity that can be useful in other areas as well. For example, their progress in autonomous vehicle technology was able to use the functions of machine learning algorithms. This algorithm understood how advanced sensors built into an autonomous vehicle could be used to take measurements from its human passenger.

These measurements could be easily taken by applying controlled and prescribed force in the vehicle causing specific movement of the passenger. All this would give a log of various health checks – core body balance, body temperature and responses to certain stimuli that could be used in advance to signal or denote various ailments.

Manufacturing and Industrial Use

Applications such as cloud computing, Machine Learning combined with Big Data are all contributing to the smart and intelligent worker in the form of a bot which can do no wrong. Industrial lines of work such as oil rigs, heavy construction and other projects are making use of data-driven technology which signals and indicates real-time issues that can reduce breakdown, reduce the project timelines and cost overruns.

It also helps in precision tooling.
One can see the ubiquitous nature of Artificial Intelligence in everything around us. It will be no surprise that we see repetitive tasks being done by AI-based machines all around the world. For an engineer on the field, the AI bot will be the second brain he can pick to do complex calculations quickly, warn him before exceeding certain errors and giving instructions. STEM (Science, Technology, Engineering and Maths) has changed dramatically owing to AI.

Related Article:

Master The Skills Of Machine Learning And Be Successful!

It’s a big deal: Machine Learning is the rave of the moment. Tons of companies are going all out to hire competent engineers, as ML is gradually becoming the brain behind business intelligence. Through it, businesses are able to master consumers’ preferences thereby increasing profits.

 

In 2006, Netflix announced a prize of $1 million to the first person to improve the accuracy of its, recommendation system by 10%.

The prize money serves as proof of the relevance placed on ML. Also, Netflix’s anticipation of substantial profits through a slight improvement in the accuracy of its recommendations.

It’s closely linked to data science: Just as humans learn from experience, ML systems learn from data. Thus, many ML engineers are made to wear two hats (machine learning engineering and data science) while undertaking their daily work , which is arguably a good thing.

As you should know, data science is rated as the sexiest job of the 21st century. Learning ML would make you more knowledgeable in data science and thus more attractive in the labor market.

To become unwary of the dangers of AI: Many things have been said about AI and whether or not it could really snatch jobs. Fortunately, however, knowledge of machine learning may take you a step towards protection from any predicted dangerous outcome of mass scale AI implementation, because, as of today, most systems are built by humans. Also, there’s will be a positive demand of engineers, come what may.

Interested in learning some cool Machine Learning already? Then you are at the right place!

Enroll for India’s Best Machine Learning + Artificial Intelligence Certification Program. It has the following things to offer:

  1. Teaches you Deep Learning as well. Both theory and projects
  2. Prepares you for the real-time job of a Machine Learning Engineer
  3. Teaches you all the required tools
  4. Helps you build projects required for Machine Learning + Deep Learning
  5. Also gets you an internship (if you are a student)
  6. It also offers guaranteed interview assistance after graduation from the course

Certification in Artificial Intelligence and Machine Learning in Collaboration with E & ICT Academy, IIT Guhawati, and Imarticus Learning

Machine learning is powered by AI. With ML, we can power programs that are easily updated and modified to adapt to new environments and tasks- resulting in quick progress on difficult projects. ML and AI are almost synonymously used in tandem when it comes to the latest tech trends. And, AI has disrupted many industries forever – like SaaS, Manufacturing, Defense, Analytics, public sector, and so on.

If you learn machine learning through the best Machine Learning & AI course, you are likely on a fast and high-growth career trajectory.

Here is why!

#1. ML & AI Are Skills of the Future

Skills in ML can affect your long-term employment prospects because the field is projected to experience rapid growth.

With the emergence of advanced technologies like the Internet of Things (IoT), Machine Learning is experiencing a certain surge in demand and popularity.

If you learn machine learning by taking up data science certifications, there is an increase in the probability that you will have better job prospects as compared to someone without ML skills.

#2. Solve Real-World Problems

There is a lot of talk about how AI will replace jobs, but the truth is it will create new job opportunities. As an ML engineer, for instance, you get to work on projects that have a big impact in the real world and lead to business solutions that are meaningful.

#3. Versatile Growth Opportunities in the Data Sciences

Machine learning and artificial intelligence (ML &AI) skills are beneficial to a data science career. Both positions give you the opportunity to let your knowledge of both fields expand. Switching back and forth between roles can quickly enable you to become an invaluable resource in today’s rapidly changing world.

You want to have an advantage as early as possible so that you can learn about solving new and undiscovered problems. When the time comes, these skills will be in great demand and allow you to secure a career path on the rise.

What does a growth path in this domain look like?

Typically, a machine learning engineering career path begins with being a Machine Learning engineer. Machine learning engineers develop applications that automate common tasks previously done by humans and take care of the repetitive ones for humans to do efficiently without error.

When you earn a promotion as an ML engineer, you are then promoted to be an ML architect! Their responsibility is developing and designing prototypes for applications that need development.

There are a few other roles in the field which one could take on as well. These include ML data scientists, ML software engineers, senior software architects, and more.

New tech arenas keep developing into this space. So, keep your interest, skills, and industry demands aligned for the best growth!

How to make a successful career in AI & ML?

Want to learn machine learning with the best Machine Learning & AI course?

certification in Artificial Intelligence and Machine Learning

Imarticus brings to you the class-leading AI & ML certification in collaboration with E&ICT Academy of IIT-Guwahati.

Our highly-rated program has fostered hundreds of successful professionals serving the industry worldwide. Your chance to be a part of this prestigious career trek begins with us.

Enroll with Imarticus now!

What Do AI & ML Engineers Do in Real World Scenarios?

Worldwide industries are identifying AI/ML engineers as one of the fastest-growing job titles. Since the trend is likely to last long, this means there are millions of opportunities for the present-day freshers and those planning a career. Here is all you need to know about what AI/ML Engineers are and what they do!

What Is an Artificial Intelligence and Machine Learning Engineer?

Over the past years, the role of an ML engineer has evolved. Typically, they are computer programmers, but their focus extends beyond programming to perform specific tasks that enable machines to take actions without being specifically directed to perform those tasks.

What does a Modern-day AI/ML engineer do?

Bridging Model-Building and Production

The general purpose of an ML engineer is to act as a bridge between the statistical & model-building work of data scientists & to build production-ready & robust AI/ML systems, platforms & services. The AI/ML Engineer use their knowledge of & combine it with programming and software engineering skills to enable easier use of and access to said models and analyses.

They may translate the work of data scientists from environments such as python/R notebooks analytics applications, automating model training & evaluation processes.

Improving Systems

AI/ML engineer is responsible for developing machine learning algorithms to improve systems or processes by automating tasks that otherwise would be physically executed. The job role demands skills in programming, analysis, & an understanding of tools & techniques used to apply AI/ML to real-world tasks. With the rapid increase in the use of ML, more programmers incline Machine Learning & AI courses that educate them in relevant techniques & tools.

Artificial Intelligence and Machine Learning coursesImproving Operational Efficiency

Machine learning engineers spend their time doing several things like exploring data, organizing, cleaning, and analyzing data to find patterns & attributes to build machine learning models.

They are a part of a brainstorming team with product managers on customer needs & are expected to come up with new ideas. AI/ML Engineers monitor and fine-tuning ML models to improving team productivity.

Task-Oriented Machine Learning

A machine learning engineer monitors, optimizes, tests, trains, and deploys machine learning algorithms for specific tasks. At some places, ML engineers are expected to implement and carry on more ML-specific transformations, such as outlier detection, dimensionality reduction, feature engineering, missing value imputation, normalization, etc. Once the data is ready for the ML algorithm, the ML engineer is responsible for setting the training algorithm appropriately and executing it in a reasonable time to produce a satisfactory performance.

Grow and Learn Machine Learning with Imarticus Learning:

Explore the opportunity to learn Machine learning from the Best ML & AI Course that boosts your Data Science Career. An industry approved program designed by E&ICT Academy, IIT Guwahati, and Imarticus Learning for future Data Scientists & ML Engineers, this program builds a strong foundation of Data Science concepts, and industry experts will help you learn the practical implementation of Machine Learning, Deep Learning, and AI techniques through real-world projects from diverse industries.

This course goes a long way towards helping you unlock lucrative career opportunities in the coveted fields of Data Science and Artificial Intelligence. The 9-month extensive program will help you prepare for the Data Scientist, Data Analyst, Machine Learning Engineer, and AI Engineer roles.

The objective of this state-of-the-art Artificial Intelligence and Machine Learning Certification Course is to perfectly prepare you for the AI and Machine Learning job roles you aspire for

For further details, contact us through Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

Jobs of The Future: Artificial Intelligence and Machine Learning

COVID-19 has inverted the ways we lived. The jolts can be felt across workplaces, particularly where it has forced organizations to reduce activities, including leisure, restaurants, oil & gas, and airlines. Throughout COVID-19, the technology industry remains strong. The pandemic spurred technological innovation and enabled many to continue work despite lockdowns & other pandemic mitigation measures.

Benefits of AI?

  • Automation: AI gives a better understanding of machines to interpret a situation or perform necessary action. Tasks can be automated with minor human intervention through AI/ML. While automation takes place, the roles requiring human attention automatically become more productive with more time to focus on them.
  • Speed: AI is efficient in expediting much work when compared to humans. AI lets us complete tasks flexibly before deadlines. This reduces human labor & provides great speed & efficiency.
  • Accuracy: AI eliminates maximum chances of error. The machine always acts according to a fixed AI algorithm; there are fewer errors in every given scenario. In short, AI defines new limits of accuracy & precision with lesser risks.
  • Exploration: AI has helped to discover many new sites, for example, volcanic sites, ocean beds, etc. Humans being vulnerable to these sites, can’t reach and survive these scenarios. Robots are meant to go to these places and collect data.
  • Data Collection & Analysis: Data analytics is the future technology in today’s business world. Industries & businesses analyze valuable chunks of data & extract helpful information.

Applications of AI?

Artificial Intelligence and Machine Learning courses in IndiaAI is applicable in every conceivable field & recent advancements are increasing the relevance of AI in every sphere. Here are the top applications of AI:

  • Speech Recognition: AI allows us to convert spoken words into digital content. Speech recognition has various uses like voice-enabled messaging, content writing, voice-controlled remotes, & appliances. Speech recognition is also used for authorization & validation.
  • Natural Language Processing: NLP enables a machine to understand the human text. Virtual assistants like Siri, Google Assistant, Alexa, are all an example of chatbots working on the principle of NLP.
  • Stock Trading: There are AI platforms that allow automated stock trading. With the algorithms, these bots understand the fluctuations in the stock market & predict high-return stocks with more accuracy. The future scope of AI/ML in the finance sector is fuelled up due to the increasing craze for cryptocurrency.
  • Robots: Besides developing intelligent robots, AI has created robots that assist humans with routine tasks like cleaning, gardening, serving, etc.

Explore Careers in Artificial Intelligence with Imarticus Learning:

Freshers need to realize their competencies & acquire skills for AI roles with chances of upward mobility in career. The future scope of Artificial Intelligence is increasing due to new job roles & advancements in the AI sector. 42% of the IT workforce in India will require upskilling or reskilling by 2025. Imarticus Learning offers artificial intelligence and machine learning courses and machine learning certification courses to upskilling & and stay relevant.

The program builds a strong foundation of Data Science concepts. Industry experts will help you learn the practical implementation of Machine Learning, Deep Learning, and AI techniques through real-world projects from diverse industries. The 9-month extensive program will help you prepare for the Data Analyst, Data Scientist, Machine Learning Engineer, and AI Engineer roles.

This state-of-the-art Artificial Intelligence and Machine Learning Certification Course aim to let students learn machine learning & prepare for future jobs.

For further details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

4 Industries Where Artificial Intelligence is Making a Huge Impact

Artificial Intelligence has been the next best thing to revolutionize the world we live in. Once a distant dream, AI is now a reality owing to higher and far more powerful processing powers and advances in the field of machine learning. The applications of AI are bountiful and range over many areas. Here are some of the areas where AI is working wonders.

Healthcare

AI surpasses human capabilities when it comes to processing massive amounts of data efficiently and accurately in a matter of seconds or minutes. This can become indispensable for the medical sector. There are AI-powered apps such as Ada and Babylon where users can enter their symptoms, and the apps use data analytics to offer the users a medical consultation. AI can also generate customized treatment paths for patients depending on their medical histories, genetics, and symptoms. Since AI is based on machine learning algorithms, the more data you feed, the more accurate the results will be. In a field where the question is often about saving someone’s life, using systems that are quick, efficient and free of human error will go a long way.

Security

Another critical area where AI is increasingly deployed is security. The amount of data being stored in the cloud has given rise to some severe cyber security concerns. AI, through a combination of data analytics and machine learning, can offer protection from hackers by automating the intricate process of detecting and preventing breaches. This can be done with the speed and accuracy that lie beyond human ability. Since it uses machine learning that mimics humans’ experiential learning, AI-powered security systems are getting progressively sophisticated and powerful as they analyze more data. This also makes it more difficult for hackers to steal or corrupt data. However, technology has its limitations, and it is possible for AI to lose against a hacker so a combination of humans and AI can proficiently combat the increasing security threats.

Education

Another field where AI has an increasing influence is in the area of education. One of the primary uses of AI is in grading – a very time-consuming job that often might have errors. Deploying AI-powered machines for grading objective questions like multiple choice questions can save a lot of time. This can also be used across a wide range of students from school to graduate students. AI can also be used to analyze large amounts of data and develop personalized lessons for students based on previous learning patterns. Each of us learn at different paces and need different techniques and AI can do precisely that. It can also focus on places and subjects we lack in and thus revolutionize education as a whole. AI cannot replace teachers as a whole but can help them better the experience for students.

Human Resource

One of the most fundamental jobs of HR is that of recruitment. An HR department might have to go through loads and loads of applications which can be very time-consuming and stressful. Additionally, as psychology has time and again points out, humans are often subject to biases. AI can swiftly find the best candidates for a position based on processing all the data on the candidates’ CVs. AI is also devoid of the human element of bias. AI can also find possible risk areas of performance through data analytics of the employees. Moreover, it also can use available data and machine learning to offer decisions that would be best suited for the company.

AI has the potential to empower us and be a game-changer just like wheels and electricity were all those years ago. It’s just a matter of how we use it.

Related Article: The Promise of AI: Application in Education and Health Care Sector