Contact Us
×

Tag: data mining

Does Machine Learning Excite You? Check Out Our Data Analytics Course!

Posted on by Imarticus Learning

Machine learning (ML) is truly a blessing to modern computing and technology, possessing the ability to endow systems and machines, the ability to think for themselves and tackle tasks on their own without any supervision of humans. Machine learning is able to do this by creating artificial neural networks which simulate how human brains work. Machine learning is assisted by data science and supports its applications in various fields.

Even though machine learning was initially invested upon with the primary focus on Artificial Intelligence, it was later recognized as a separate field and started being heavily invested upon from the 1990s and is one of the most valuable fields of computing that has one of the highest industry requirements of skilled professionals and freshers holding expertise in various skills and tools which assist in machine learning.

In this article, we will learn more about machine learning and how a well-planned data analytics course can help you progress in your career if you are already in this field or how it can help freshers get exposed to ML. 

What is machine learning?

Machine learning first came into existence due to the interest of having systems and computers learn from data on their own. “Machine learning” was first termed by Arthur Samuel in 1959, who was working in IBM at that time. During his tenure there, he was responsible for various important projects related to computer gaming and AI. It all started when Mr. Samuel took the initiative to teach computers how to play games through the game of Checkers on IBM’s first commercially available computer, the IBM 701.

Eventually, machine learning started being used for various purposes and borrowed many models and approaches from statistics and probability theory. AI uses predictive analytics along with machine learning to execute the various responses or trigger actions. All of this is acquired from the training data set which helps the machine in learning and equips it with the information.

Machine learning is an important branch of computing and data science that creates autonomous systems which learn from data on their own. A machine trained with clean processed data eventually identifies trends and patterns to respond to situations without human supervision.

Machine learning also promotes the automatic improvement and development of algorithms or data models which improve on their own. Machine learning is an important part of Artificial Intelligence which uses data mining, predictive analytics, and various tools to assist machines in learning more extensively with methods like deep learning to allow them to execute functions that emulate the responses of a human, just much more accurate and fast.

Machine learning is also not biased unless specifically asked to do so, hence promoting unbiased AI-supported systems that make fewer errors. Data mining is also a very relevant field and quite valuable to machine learning as it helps systems come to conclusions without having some bits of data or having unknown bits of information. Machine learning is a type of predictive analytics which is backed by data and is exploratory in nature.

Perks of a Data Science Prodegree from Imarticus

The Data Science Prodegree is a great data science course that students and working professionals can choose to gain more exposure and skills in the fields of machine learning, business analytics, and AI.

 

  • Acquire skills and learn how to use required tools and algorithms
  • Gain valuable industry and course certifications
  • Get placement support and opportunities from the best companies
  • Advanced live classroom learning supported by technology and real-life projects

 

Imarticus’s Data Science course with Placement is a great choice if you wish to advance in your career and learn about machine learning, AI, business analytics, or data analysis which will help you become more effective as a data scientist and pursue your dream career in this respectable field.

Why is Data Science a Good Career in 2021?

Posted on by Imarticus Learning

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 Data Analysis and Data Science?

Posted on by Imarticus Learning

Following the current technological transformations within the economy, there has been an emergence of enormous career options, wherein, Data Science is the hottest. According to the Glassdoor, Data Science arose as the highest-paid area. On the other hand, there is a significant field that has been gazing attention for years, i.e., Data Analysis. Both the Data Science and Data Analysis is often confused by the individuals.

However, the terms are incredibly different in accordance with their job roles and the contribution they do to the businesses. But, are these the only factors that make these two distinct from each other? Well, to know more we need to take a look below:


t
Also Read: Top 5 Data Science Trends in 2018

Data Analysis Data Science:

Data Analysis is referred to as the process of accumulating the data and then analyzing it to persuade the decision making for the business. The analysis is undertaken with a business goal and impact the strategies. Whereas, Data Science is a much broader concept where a set of tools and techniques are implied to extract the insights from the data. It involves several aspects of mathematics, statistics, scientific methods, etc. to drive the essential analysis of data

Skills:

The individuals misinterpret Data Analysis with Data Science, but the methodologies for both are diverse. The skillset for the two are distinct as well. The fundamental skills required for Data Analysis are Data Visualisation, HIVE, and PIG, Communication Skills, Mathematics, In-Depth understanding of R and Python and Statistics. On the other hand, the Data Science embed the skills like – Machine Learning, Analytical Skills, Database Coding, SAS/R, understanding of Bayesian Networks and Hive

 

Techniques:

Though the areas – Data Analysis and Data Science, are often confused about being similar, but the methodology is different for both. The methods used in the two are diverse. The essential techniques used in Data Analysis are – Data Mining, Regression, Network Analysis, Simulation, Time Series Analysis, Genetic Algorithms and so on. While, the Data Science involves – Split Testing, categorizing the issues, cluster analysis and so on

Aim:

Just like the areas are different, so are their goals. The Data analysis is basically about answering the questions generated, for the betterment of the businesses. While Data Science is concerned with shaping the questions followed by answering The Data science, as illustrated above, is a more profound concept


The era of Artificial Intelligence and Machine Learning is shaping the economy in a much more comprehensive aspect. The organizations are moving towards a data-driven decision-making process. The data is becoming imperative in functioning and is not limited to the Information Technology organizations.

It is soon taking over the industries like – Sports, Medicine, Hospitality, etc. Such technological advancements have led to a rise in job opportunities in the area of Data Science and Analysis. The merely significant facet which needs to be taken into consideration is the understanding of the difference between the two. Big Data is the future which is expected to lay a considerable impact on the operations of both industries and routine life.

Related Article: What a Data Scientist Could Do?

Data Literacy Is Very Much a Life Skill– Here Are 4 Reasons Why?

Posted on by Imarticus Learning

The world is no stranger to data; in fact, in recent times, the world has found itself being bombarded by more facts and statistics than ever before. At quite the same speed, people have also been faced with fake facts, viral social media forwards with little to no truth.

Being data literate has moved from being a niche requirement to being a life skill that allows people to distinguish between fact and fiction. Data literacy is a way of exploring and understanding statistics in a manner that provides meaning and insight.

This meaning isn’t relegated only a data science career or to businesses looking for an edge over competitors. It applies to society and its interconnected systems as a whole.

To drive the point home, here are a few advantages that data literacy offers when looked at as a life skill:

Recognising the Sources of Data

Data is everywhere, especially in a world where nearly everything is digital and produces and consumes more data. There are many different ways in which data exists, including graphs, images, text, speech, video, audio and more. Recognising the different sources of data is the first step towards working with data. The sources, formats and types all have a role to play in determining the use (and potential misuse) of data, which in turn drives data literacy.

Acknowledging the Self as a Consumer and Producer of Data

The messages you send, images you post and likes you leave on social media are examples of data. So are the transactions you make and the searches you conduct on search engines such as Google and Bing. Today, nearly every single person in the world is a data producer; those sources of data are vital to value-generating processes across industries and markets.

Similarly, people are daily consumers of data even if they don’t perceive it as that. The COVID19 pandemic has brought this into the light even further– front page statistics are at the back of everyone’s mind, as are the names of containment zones and the best practices for sanitisation.

Recognize Biases and Fallacies

Data literacy gives the people more agency to call out those producing statistical data that is biased, twisted or outright incorrect. As citizens, consumers and valued members of a society, it is imperative that every individual is able to identify false promises or glossed-over issues that allow wrong-doers to continue as they were.

Data ScienceData literacy gives people the power and the evidential backing to call out those intentionally or unintentionally propagating mistruths and fallacies through awry statistics. This way, data literacy plays a pivotal part in politics, economics and ethics of a society, indeed of the world.

Improves Data Storytelling

Instead of data points presented on their own, data that is presented as descriptive stories make individuals more likely to understand the effect, decipher trends and make more educated decisions. While data storytelling is imperative to learn for those taking a data science course, it is just as important for members of all other fields to better present their arguments such that they catch eyes.

Data has never been a strictly academic factor; however, it has often been painted as complicated, invasive or unnecessary to penetrate everyday lives. Data storytelling ensures that data is taken even further out of that box and presented as actionable insights to even the average Joe Bloggs.

Conclusion

The focus on data science and literacy shouldn’t just be restricted to mathematics and algorithms but everyday applications of data in daily lives. Data understanding allows people all over the world to take more control of what they’re producing and consuming. Data fluency and literacy is achievable by all.

Do You Know Data Science Professionals Been Hired The Most ?

Posted on by Imarticus Learning

Data science courses have become increasingly popular in the past few years. That’s because the demand for data science professionals has risen substantially in various industries.

Companies in various sectors recognize the importance of big data and want to use it properly. In the following points, we’ll look at the sectors that hire the most data scientists:

Industries that hire the most data scientists

There are several industries involved in hiring data scientists:

Finance

The finance sector utilizes the expertise of data science professionals the most. It uses data science in determining the growth prospects of its investments, to calculate risk, perform predictive analysis and manage its operations.

Banks also rely on data science to detect and prevent credit card frauds. They use data science to track fraudulent behavior patterns in suspicious clients to identify potential credit card frauds.

When you join a data science course with placement, you’ll surely be working on finance-related projects.

Healthcare

Data scientists work in different avenues of the healthcare sector. Mostly, they work in the research aspect of healthcare and contribute to making trials and testing more efficient. Data science and artificial intelligence help companies in reducing errors and enhancing the efficiency of research processes.

Modern healthcare technologies also utilize the data science to provide better experiences to patients. Data science helps in improving the accuracy of diagnoses and delivers more precise prescriptions to patients.

Entertainment

OTT platforms have revolutionized the entertainment industry. Netflix, Amazon Prime, and Hotstar are now some of the biggest entertainment companies in the world. Netflix has been using data science since it launched its digital subscription service and has been a hot topic for case studies in data science courses in India. It relies on data science to attract more customers, create high-quality content and track its growth.

Data Science Course with Placement in IndiaHow to capitalize on this opportunity

As you can see, the demand for data scientists is constantly growing in multiple industries. Whether you want to enter the entertainment sector or the banking industry, becoming a data scientist will help you in your pursuit.

The best way to start your career in this field is by joining data science courses. While there are many data science courses in India, it’s vital to pick one that suits your requirements and aspirations. You should always check the data science course details, including the data science course fees to ensure they match your criteria.

Currently, it would be best to pick an online data science course in India because it would teach you all the required concepts and skills digitally.

Enrolling in a data science course in India would not only teach you the necessary skills, but it will also make you eligible for pursuing data science roles in various companies.

You can also look for a data science course with placement. It would help you kick-start your career as a data scientist easily and quickly.

Conclusion

Now, you have learned how data science helps numerous industries. You also found out how joining an online data science course in India can help you capitalize on this demand and become a sought-after professional.

Do check out our data science course details such as the data science course fees, if you’re interested in a career in this field.

Become A Data Scientist And Start Your Career With A-list Firms !

Posted on by Imarticus Learning

Become A Data Scientist And Start Your Career With A-list Firms !

If you’re wondering why data science courses have become so popular recently, then it’s because the demand for data scientists is very high among A-list firms.

In the following points, we’ll discuss some of the biggest companies that hire data scientists and how you can start a career in one of them by taking an online data science course in India

Top companies that hire data scientists

Microsoft

If you’re using a PC, then you’ve probably heard of Microsoft already. Microsoft is a software development company and powers millions of computers throughout the world through its Windows operating system. The average pay of a data scientist at Microsoft is $136,000 per year.

Uber

Uber is an online cab-hailing service that has become widely popular due to its innovative solution. It uses data science to improve its operations, optimize route selection for drivers, calculate better fares, and a plethora of other tasks. The average pay of a data scientist at Uber is $139,000 per annum.

Pinterest

Pinterest is a social media platform for sharing and finding images. Social media platforms require the expertise of data scientists to help them enhance their algorithms and offer a better customer experience to the users. The average pay of a data scientist at Pinterest is $212,000 per year.

Google

Google is probably the most popular tech company in the world. It is also among the best employers for data scientists. The average pay of a data scientist at Google is $138,000 per year. Being a simple search engine, Google has expanded into a large tech enterprise with various subsections.

How to become a data scientist

As you can see, becoming a data scientist can help you bag lucrative jobs in some of the world’s top companies. Starting a career in data science is quite easy as well.

You will need to join a data science course in India to learn the necessary skills for this role. Online data science courses have become increasingly popular among students and professionals alike who want to start a career in this field.

You should look for data science courses in India that teach you the latest in-demand skills such as R, statistics, predictive analysis, Hadoop, and Spark. It would be best to get a data science course with placement support. When you join a data science course with placement support, you get the opportunity to start your career right after completing the online data science course in India.

Be sure to check the relevant data science course details (such as data science course fees and eligibility requirements) while looking for data science courses in India.

Conclusion

The companies we talked about aren’t the only ones that hire data scientists. Data science professionals work in numerous sectors as well, including finance, education, healthcare, and manufacturing.

Online Data Science Courses in India

Now, you know that you can start a career in this field by taking a data science course in India, you should head to our site where you’ll find more data science course details, including the data science course fees, requirements, and curriculum.

Data Scientists Are in Great Demand And Are At The forefront of The AI revolution.

Posted on by Imarticus Learning

Data scientists are in great demand due to the value they offer to Artificial Intelligence and Machine Learning. With the advent of automation and the increased focus on Artificial Intelligence, organizations and corporations are looking for skilled human assets who have expertise in this field.

In this article, we will cover how a Prodegree in Data Science from Imarticus can help a budding data scientist advance further in the field of AI and Machine Learning. Budding data scientists can utilize an extensive data science course like Prodegree by Imarticus to gain the necessary skills and knowledge that is needed to work with valuable projects and organizations.

Data Science CoursesWhat is Data Science?

Data science is a specialized field of computing and working with data, which promotes data-centric or data-backed business and IT solutions. Data science consists of fundamental methods, tools, and algorithms that use data analytics, data mining, sourcing data, creation of models to work with data, and the execution of IT processes or data models to provide business solutions or attain insights.

Data Science also powers analytical methods which allow individuals to use business analytics and predictive analytics to come to resolutions from the generated insights. Data scientists are also responsible for the process of importing data from various sources and cleaning the data to allow this data free of noise to be used in various applications.

What is Artificial Intelligence?

Artificial Intelligence is the ability of machines or systems, which allow them to take actions based on historical data and through learning on their own without any interference from humans. Artificial Intelligence uses Data Science and Machine Learning to create complex systems, which emulate how human intelligence works and responds to scenarios. Artificial Intelligence promotes automation and supports the idea of machines doing the work autonomously without any human intervention or biases.

This empowers a lot of platforms, machines, and services to provide automated services that save money for companies and allows us to give less effort by relying on rapid and efficient action taken by AI. 

For instance, AI is helping industries and factories by automating a lot of production and helping operations with AI-assisted analytics and suggestions. AI is highly appreciated even in the fields of marketing, advertising, finance, and business by making predictions to support companies in making data-backed business decisions. 

What is a Prodegree from Imarticus?

The AI and Machine Learning centric Data science Prodegree is designed by experts from this field to help future data scientists learn important data science concepts like Machine Learning and data mining, or algorithms and tools to assist in the process of building efficient models to gain valuable business insights and predictions backed by data.

The Data Science courses also offer various modules on business analytics and predictive analytics to provide analytical expertise to students. This kind of a planned data science course encourages individuals to get into this highly valuable field and learn the fundamentals required to build a great future centered on data science and AI.

A Prodegree from Imarticus helps budding developers and data scientists bag valuable job roles offered by reputed organizations like KPMG, Genpact, Infosys, and TCS.  

Data Science Certification CoursesThis course contains real projects, which will allow students to gain hands-on experience to tackle IT challenges and business problems. With this kind of well-planned course and study modules, one can truly get ahead in his or her career and discover new prospects. 

Conclusion

Working with AI is fun and interesting as well, and Imarticus is a great learning hub that promotes advanced data science and involves enrolled students in real-world AI projects. This further contributes to their skill development and exposure to this highly interesting field. AI has huge potential and a great future ahead, and this well-orchestrated course can certainly help in building your career in this field. 

Here Are Some Data Science Careers Which Are Enhancing Our Future!

Posted on by Imarticus Learning

With the increasing reliance on data science by major corporations and the biggest brands, Data science is the prime focus of this decade. Data science is making our future better by enhancing our life in various ways and through various services.

There are different careers like data analysts, business analysts, and data scientists that one can pursue to contribute to this truly interesting field which has a huge effect on our lives and will affect our future in the years to come. Similarly, data science promotes and supports IT and the efficiency or effectiveness of businesses.

In this article, we will cover how data science is enhancing our future and the various respected careers with job roles that are highly in need of being filled. 

How Data Science is improving our future

There are a variety of ways that data science is improving our future; ranging from its applications in medical science to rapid accurate resolutions to troubled customers, data science is responsible for making our lives faster, safer, and smoother in general. For instance, data science is helping the health industry by allowing patients to be treated more effectively by analyzing historic data of patients.

It is also helping medical science by empowering chemical synthesization and simulating the effects of medication on affected individuals or allergies. Data science is increasing safety and cutting risk for us as well with applications in automated braking systems, AI in navigation, and automated cars, warning about industrial risks or any issue with the structural integrity of physical or digital units.

Data science makes our lives smoother by providing assistance in machine learning of customer care or service platforms which in turn give us rapid and precise resolutions. Data science powers the recommendation engines during shopping, social media and search or media recommendations by learning our behavior and global trends and then using AI to provide us suggestions.

Highly regarded Data Science careers valued by companies and the beneficiaries 

A data science course helps individuals acquire the necessary skills to contribute to this highly reputed and valuable field that works with data. 

Data Science JobsData Scientist – A data scientist helps while sourcing the data and then processing the data. Data scientists are experts in data mining and are responsible for removing the noise from the data, handling the data, modeling the data, and storing the data.

 

  • Data Analyst – Data analysts also engage in data mining, data cleaning, and then working on the data with various tools. Data analysts then analyze the data and then use predictive analytics to gain insights from the data with various tools and simulations with the help of the acquired data.
  • Data Engineer – Data engineers work with scripts for injecting data from various sources, they are involved in the modification of data, creation of data models and they work on the data with various programming languages. They also troubleshoot data problems and assist IT or software development projects.2. Business Analyst – Business analytics is highly used by organizations to gain insights from data, and then with their help, companies make business decisions based on the visual or graphical representations and predictive analytics which is backed by data. Business analytics helps businesses a lot by helping them make the right decisions which helps them cut costs or maximize profit while minimizing risk. 

 

 

  • Marketing Analyst – A marketing analyst uses analytics to find our market patterns and the user or target behavior to help companies accurately target ads and marketing promotions. Marketing analysts depend on data to figure out trends and target the relevant audiences. 

 

It is due to data science that we are able to enjoy the various forms of technology and automated or AI-powered services that are backed and powered by data science. An expertly orchestrated data science course can help in acquiring various job roles that are in need to be delegated to human assets trained extensively in data science. 

Data Science and Analytics Career Trends for 2021!

Posted on by Imarticus Learning

A career in data analytics and/or data sciences is presently in extreme demand. This is due to the need to optimize new modes of data collection to identify large-scale problems and find solutions in a world after Covid-19, despite a minor drop in job openings at the start of the worldwide lockdown.

data analytics career

There are several trends that one must look out for if he/she wishes to pursue a career in data sciences and/or data analytics, including and beyond ones that involve adjusting to the ‘new normal.

It can be argued that 90% of data that is generated and collected were over the past 3 years. The demand for data science and analytics is therefore only going to grow in demand, at least for the next 10 years (and probably more). To ride this wave of opportunities in jobs and research and beyond, one must keep up with career trends relating to these fields.

What are the trends one must keep up with to enter a career relating to data?

  1. Understanding Data Collection

One must take a look at the avenues which entertain the possibility of data collection – preferably in new, never-before-seen ways. One may look to his/her area of expertise and collect data on it while combining newly learned data management skills to become a data analyst and/or scientist. This may definitely be aided by undertaking programs like data analytics courses at Imarticus learning.

  1. Analytical Problem Solving

In addition to hands-on experience, data analytics online learning may cover various fields relating to data. One must learn the basics like spreadsheet management in order to tabulate data more efficiently for analyst work.

Data Analytics Career

It is a useful skill to know what to recognize as possible data and convert that into an absorbable format, which will ensure later calculations, problem identifications, and solutions.

  1. Understanding Data Management Tools

If one is more interested in being a data scientist, then he/she must work to observe trends in big data. This involves learning big data management tools like Hadoop to find newer frameworks to collect, store and make sense of data. With earning SQL and no-SQL programming in addition to managing databases, one may find new problems to solve, whether for research or for aiding a business (or one of the myriads of other uses).

  1. Machine Learning

This is further aided by mastering other tools like machine learning and artificial intelligence. There are various tools that one may incorporate into his/her data studies, be they included in basic data science and/or data analytics courses or not. Undertaking this endeavor will allow one to master various avenues for finding and exercising ideas, which the world will go on to greatly benefit from.

  1. Communication

A possibly surprising trend that can be observed in regular data analysts and data scientists is the presence of soft skills. Someone dealing with data is required to regularly articulate and advertise new ways of improving things in his/her burgeoning field. Skills like effectively communicating one’s ideas and building useful chains of interpersonal relations go a long way in aiding the career of a data analyst and/or scientist.

  1. Artificial Collection of Data

One must find ways for his/her data collection and processing models to work without his/her presence. This process involves training replacements – both artificial and human. Ideally, a data scientist is expected to design systems that function without his/her interference, not only to undertake routine tasks but also to identify new problems and calculate possible solutions. A noted data trend is the undertaking of this process.

Conclusion

In conclusion, one can say that he/she must observe several trends relating to data on a regular basis, to adapt and grow into the self that can make a huge impact on this frontier field.

Data Analytics CareerData science and analytics are making strides in the tech market, and it is clearly the future. So, a career in data analytics can be really fruitful in the long run.

10 Data Science Careers That Are Shaping the Future!

Posted on by Imarticus Learning

Data is wealth in modern days and data scientists will be in huge demand in the coming years. Firms require skilled professionals to analyze the generated data. Data analysis is also predicted to surge with the rise of new-age technologies like machine learning, artificial intelligence, etc.

According to reports, there is a shortage of expert data scientists in the market. One can opt for a post-graduate program in machine learning to gain the skills needed in the data science industry.

Let us see about ten data science careers that are shaping the future.

Data Scientist

Data Scientists have to organize the raw data and then analyze it to create better business strategies. Data is analyzed for predicting trends, forecasting, etc.

Data science careerData scientists are technical personals who are fluent in data analysis software and use them to predict market patterns. Firms will require more skilled data scientists in the future due to the need to process & analyze big data.

Business Intelligence Analyst

Business Intelligence (BI) analysts & developers are required to create better business models. They also help in making better business decisions. Policy formation and strategy development are key responsibilities of a BI analyst. Firms have to face market disruptions and need good business models/strategies to tackle them. BI analyst/developer will be in demand in the coming days.

Machine learning Engineer

Machine Learning (ML) Engineers are required for creating better data analysis algorithms. They have research about new data approaches that can be used in adaptive systems. ML engineers often use other technologies like deep learning, artificial intelligence, etc. to create automation in data analysis.

Applications Architect

Firms require good applications and user interfaces to run business processes smoothly. Applications architects choose or create the right application for their firms. Due to the rise in the complexity of data, firms will require better applications to manage it.

Statistics Analyst

A Statistics analyst or statistician is required to interpret the data and present it in an understandable way to non-technicians. They have to highlight the key insights in big data to stakeholders/fellow employees. Data analysis results are also used to make predictions and identify potential opportunities. You need to be good with numerology if you are thinking to become a statistician.

Data Analyst

They have to convert large data sets into a suitable format for data analysis. They also help in finding the data outliers which can affect the business. There is a lot of data generated every day as humans analyze less than 0.5 percent of data produced! Data analysts are already in huge demand in the data science industry.

Infrastructure Architect

Infrastructure architect in a firm makes sure that the applications, software(s), databases used by the firm are efficient. Infrastructure architects also help in cost optimization. They make sure that their firm has the necessary tools for analyzing big data.

Data Architect

Data architects mainly focus on maintaining databases.

Data Science CareerThey attempt to make the database framework better. With the rise of automation in data science, data architects are in huge demand to provide better solutions.

Enterprise Architect

Enterprise architects are IT experts and provide firms with better IT architecture models. They suggest stakeholders & senior managers in choosing the right IT applications for data analysis. Top companies like Microsoft, Cisco, etc. hire enterprise architects for maintaining their IT framework.

Data Engineer

Data engineers are required to create a good data ecosystem for their firms where the data pipelines are maintained. Data Engineers are required to choose better data analysis applications to provide real-time processing. They also help in making the data available to data scientists.

Conclusion

Data science is a growing field and there are a lot of job opportunities. You can learn Data Science Courses in India from a reliable source like Imarticus learning. One can also target any particular job role in the data science industry and should learn the necessary skills. Start your post-graduate program in machine learning now!