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Category: Analytics

Covid-19: How Imarticus Learning Successful in Online Learning That Compensates For Campus Experience?

Posted on by Imarticus Learning

COVID-19 has set many new normal in almost all aspects of life. Learning is one of those areas which are severely affected by COVID-19. When the global health crisis set its foot in the country, it jeopardised the dreams of thousands of students who were looking forward to exciting campus life. Campuses shut down when the pandemic started to spread in the community, taking away the best thing students love about the campus education – the campus experience.

When the government called for a lockdown, inevitably, all campuses had to opt for online classes. Needless to say, it was a huge blow to the students’ expectations of an exciting academic year. While many campuses struggled to match the experience an active campus life can offer, Imarticus Learning made a distinctive mark by providing unmatched experience through their distance learning programs.  Here is how they did it.

On-Campus Course Vs Online Learning

On-campus learning has many perks as compared to online learning. The most important one is the peer-to-peer interaction. It opens the windows to a wider world, with every student bringing their bit of knowledge to the campus ecosystem, and discuss everything from the syllabus to career opportunities.

Another factor that sets campus education apart is the involvement of faculties in the learning process. Learning from a teacher has more advantage over self-learning. Direct interactions and doubt clearing sessions are the best part of campus education.

Career fair and campus interviews are something every student look forward to. Many campuses offer placement assistance and conduct orientation sessions to help their students secure a good job as they finish the course.

Distance learning generally lacks all these perks. Traditional distance learning courses offer little support to the students. All they get is a set of reference materials which they can learn at their pace. While some online courses offer contact classes and assign projects through their off-campus centres, others just send a set of reference material to the student.

Imarticus Learning

Online Learning

Imarticus Learning has a completely different approach to distance/online learning. The distance education programmes are designed in a way that mirrors the regular on-campus courses. They adopt an industry-first approach to ensure better employability after the course. The state-of-the-art online learning system with highly tech-supported classes make the courses no less than the regular classes.

Alumni Network and Mentors

One of the striking features that differentiate Imarticus from their competitors is a strong alumni network of more than 35,000 ex-students. Many are industry experts and are good resources to approach when you complete your course and become market-ready. While this alone is a good support network, there are more than 100 active mentors offering guidance to the students. These stalwarts will help you understand the respective industry, help you accustom to the industry standard and trends and respond to your concerns and doubts regarding your career.

Placement Assistance/ Guarantee

Imarticus has successfully developed associations with more than 480 global firms. This enables them to offer an interview guarantee or assistance depending upon the course selected.

Revolutionizing Online Learning

Imarticus has been revolutionising online learning with their innovative approach and guaranteed job assurance. Recently, they introduced an ISA model, where the students need to pay their course fees only after securing a permanent job with a minimum salary package of ₹500,000 per annum. The fees can be paid in 36 installments each payment amounting to 17% of their monthly income at 0% interest.

Partnering with Market Leaders

No matter how good your curriculum and knowledge base are, relevant experience is what gives you an edge in the job market. Imarticus has partnered with market leaders like KPMG to help the students jump over this hurdle. The students will get to deal with case studies from the partners thus dealing with real problems and finding feasible solutions.

With the right approach, newest technology, and a wonderful supporting structure, Imarticus has proved that online classes can be as productive as the on-campus courses, if not more. They have invested in an innovative approach to help their students to have an edge over their competitors while racing for an opportunity.

Pursue a Career in Data Science: Why Is This The Perfect Time (COVID – Pandemic)?

Posted on by Imarticus Learning

In a recent article published by LinkedIn, the organization reported a 25% increase in the number of data science professionals in India alone. On a global scale, this number is close to 37%. If you have been wanting to pursue a career in data science, then now is the right time to chase that dream, and in today’s article, we will tell you why?

Let’s get started.

Why Should You Pursue a Career in Data Science in 2020?

Post the COVID-19 crisis, the world has shifted to a completely remote work environment, and as predicted, the amount of data that is available now for collection has increased rapidly. As companies keep collecting a variety of different data sets, the need for expert data scientists are swiftly on the rise.

Career in Data Science in COVID 19 PandemicThe key concept behind this rise being, companies, need experts to analyze the data that is being collected and conclude decisions which not only contribute to short term gains but also long term business advances for the business.

Along with this, since the demand for such roles is on the rise, companies are willing to spend more to hire the best talent in the market, thus increasing the overall pay of the profession.

 

Some of the most common designations you can explore in this field include the following:

  1. Data Engineer
  2. Data Analyst
  3. AI Product Manager
  4. Data and Analytics Manager
  5. Database Administrator
  6. Business Analyst

How to Get Started With a Career in Data Science?

Now that you know the why of why you should pursue a career in data science, along with a few of the designations you should pursue, let us explore how you can kick start your career.

21st century is one of the hottest times to pursue a career in data science since millions of job openings are being posted on the regular. While having a degree in science or engineering is a good foundation to pursue a career in data science, if you truly want to stand out, one of the best things to do is to get a professional certification from any of the top recognized companies.

While one of the most obvious advantages of having a certification in data science is the edge it gives you over thousands of applications; the underrated advantage is making it easy for recruiters to spot your talent and choose for the right role.

Conclusion

2020 is a cornerstone in shaping how big data analytics will be used in the future, and thus the decisions you make today on how to pursue and shape your career in data science will determine your success in the future. With technologies such as big data, machine learning and artificial intelligence being readily used by the small to medium scale businesses around the world to increase their capabilities, the need for skilled professionals, who can swiftly analyze this data and extract meaningful insights will be on a constant rise.

In 2020, if you choose to pursue a career in data science, it can easily be estimated that your future will be secure for the next generation.

We offer data science courses at our centers in Mumbai, Thane, Pune, Ahmedabad, Jaipur, Delhi, Gurgaon, Bangalore, Chennai, Hyderabad, Coimbatore.

Are Business Analysis Certifications Worth Earning?

Posted on by Imarticus Learning

Business analysts are typically assigned the task of determining whether products and projects are strategically viable. The role involves collaboration, strategic planning, as well as top-tier communication skills. When it comes to hard skills, however, knowledge of Oracle or Hadoop and similar frameworks are often valued highly. This is especially so if the company you’re applying to works with tonnes of data and needs someone familiar with both software and the business side of business analysis.

That said, it is worth exploring whether a business analysis certification adds value to your resume or is just a waste of time and money. It is also worth evaluating whether all the business analysis certifications out there do what they claim to do or don’t add much to your CV.

If you’re not sure whether to take the leap or not on a business analysis certification, read on:

Popular Business Analysis Certifications

Most businesses prefer hiring people who have certifications covering Oracle and Hadoop, along with other data analysis techniques. The most preferred certifications in this field are the Certified Analytics Professional (CAP) and Certified Data Science (CDS)– they also happen to be the ones that are most consistently opted for by rookie business analysts.

Other than these two, there are other certifications with different focus areas. They include:

  • ECBA (Entry Certificate in Business Analysis)
  • CBATL (Certified Business Analysis Thought Leader)
  • CBAP (Certified Business Analysis Professional)
  • CCBA (Certification of Capability in Business Analysis)

The Benefits of Getting a Business Analysis Certification

  • They’re given importance during recruitment processes: Business analysis certifications are especially helpful for professionals who have a bachelor’s degree but don’t intend to study further. Indeed, the majority of job postings for business analysis roles ask for a bachelor’s degree and a certification instead of a higher-level degree. This shows that employers are putting more emphasis on skills and industry-grade learning rather than advanced academic qualifications.
  • They display niche expertise: Getting a business analysis certification often involves training for a niche software, skill or project approach within the larger business analysis umbrella. Companies today are on the lookout for professionals who can solve problems and work with specific software such as those put out by IBM, Azure, Amazon and Oracle cloud. Certifications in these domains indicate to companies that you’re proficient and have an industry-standard certificate to prove it.
  • They keep you relevant: Certification may once have not been the norm, but companies are increasingly looking for certified professionals who have gone the extra mile to validate their skills. This is especially so during crises, where the large-scale changes and hordes of data can leave businesses stumped for insights and strategies. Certifications can be added on at every stage of your career to enhance your resume with every corporate rung you climb.
  • They give you industry exposure: The best certification courses are the ones that are either vetted by industry leaders or have been created in collaboration with them. This industry exposure is invaluable when it comes to leaving your mark in such a competitive world; it displays that you’re well-versed in both theory and practice. It shows that you are capable of solving real-world problems and are aware of the industry dynamics to such an extent that you can hit the ground running in your new role.

The Final Verdict

The bottom line of this debate is that business analysis certifications hold a lot of value for professionals looking to jumpstart their career, switch roles or advance up the corporate ladder. Business analysis is a complex, ever-changing field so showing, through certifications, that you’re up to date and ready to work will do your job projects no end of good!

What is Business Management?

Posted on by Imarticus Learning

Business management is an umbrella term for the theory and practice that is employed on the regular when operating a business. It is interdisciplinary in that it involves business administration, marketing, finance, economics, accounting, and information systems.

On the practical side of things, business management involves planning and strategy to seamlessly integrate multiple departments such that they work much like well-oiled cogs in a machine.

A business management course certification comes in handy regardless of the size, scope, and industry of the company you choose to work for.

Business management principles are intrinsic to the growth and success of a company as they enable reduced operation costs, better employment rates, increased productivity, and seamless regulation compliance.

Depending on which level of education you’re at, you can pick one of the following degree tiers in business management:

  • Bachelors
  • Masters
  • Diploma
  • Certification

What a Business Management Course Gives You

Upon completing a business management course, you’ll set yourself up for a variety of careers in fields including accounting, finance, investing, marketing, and management. Some roles you could look into are:

  • Business Management CourseSales Manager: You’ll be responsible for training and managing a team of salespeople, often traveling to meet clients and represent the company you work for.
  • Management Analyst: In this role, you’ll be tasked with creating plans to improve management structure and efficiency.It is a strategic and analytical position that involves decision-making for better profitability & higher employee productivity.
  • Financial Analyst: This role involves analyzing individual and company investment decisions, advising on stocks, and keeping track of investment portfolios and performance.

What You’ll Learn in a Business Management Course

A typical business management course explores the basic principles of management including planning, staffing, and leadership. You will be exposed to business laws, compliance, and regulation; you’ll then move on to private and public sector finance and investments.

Some courses also explore fundamental marketing concepts, including but not restricted to market research, strategy, decision-making psychology and strategy-building. You will also come across economic principles including inflation and global financial systems.

When picking the right business management course for you, you’ll want to evaluate what they offer along with some other influential factors:

  • Business Management CourseSyllabus: Look through the curriculum to evaluate how concentrated or expansive the topics are. Depending on which level of education you’re at, you’ll find that niche courses target specific skills and are ideal for those with at least one degree.
  • Learning style: The ideal course must offer both theory and practice to enrolled students. Practical aspects could involve case studies, seminars, hands-on projects, and mentored assignments.
  • Job scope: Hopeful students must determine the weight of the degree or certification and how it influences their position against other competitors in the job market.
  • Faculty: A good course should be facilitated by faculty members who are experienced in the field and can guide students both during and outside the course. Give out brownie points for staff who have worked in a company you’d like to work at and seek them out when you join the course for guidance and mentorship.
  • Budget: Business management education can be a bit more on the expensive side. Hence, it is critical to evaluate your budget and whether the courses that fall under that budget checkboxes in the other categories stated above.

Conclusion

Business management can be studied at a variety of academic levels and concentration tiers. However, it’s safe to say that any business management knowledge can prove very helpful in the workplace and the job market!

Why Data Scientists Should Follow Software Development Standards?

Posted on by Imarticus Learning

Introduction

Technology has become the flagbearer of changes to which we are subjected to daily. Therefore, it impacts us in every possible way. How technology comes to us should mostly positively affect us. Therefore, it becomes important for the people driving this change to adhere to some pre-defined standards for improved quality of work and standardization of the same.

Data Science has come a long way. It has become one of the most popular subjects giving people the best in class in jobs and putting them in a position of the drivers of change. A Data Science course in Chennai would help you in becoming employment ready.

Data Science has enabled handling the bulk of data with ease. With Data Science you can drive different conclusions from the same set of data. You just need to change the algorithm.

Who is a data scientist?

Your Data Science career can bring a lot to the table. Initially, the word ‘Data Scientist’ was used for people who used to organize and analyze a huge amount of data. However, the role of a data scientist has drastically evolved in its due time course.

Today, data scientists develop algorithms that make sorting, compiling, and analyzing the sets of data a cakewalk. Effective data scientists have standardized the processes and have developed a standard procedure to work things out. These data scientists are technically well-equipped and can build complex algorithms which can be repeatedly used to make a task easy.

They have a strong quantitative background and are usually result oriented. Also, they have extensive knowledge of different programming languages like R, Python, Tableau, SQL, etc. As the demand for automatization is increasing, data scientists can access more and more jobs.

The need for data scientists to follow Software Development Standards

Standardization is important everywhere irrespective of the field. Therefore, these data scientists need to adhere to a specific set of software development standards that are already in place.

In the times where cybersecurity is a major issue, it is really important to have some software development standards in place. This would ensure that the new software is being designed keeping in mind these standards which will consider the safety and security of data and information of the end-users of that particular person.

Development standards have been also designed to keep uniformity across the organization. These standards ensure that the work output is generated at a certain level. Also, with software development standards, a set of consistent rules are laid down which makes the job of a data scientist quite easy.

With Software Development standards, you can use the same algorithm for different purposes with slight modifications. Also, it ensures that the program written by a data scientist is clear and understandable and adheres to the statistical principals. With standardization, codes will be written in a language that is understood by all.

Having simple rules is important. Software development standards follow a structured approach when it comes to writing a code or designing software. It bridges the gap between your research and the final product which you want to build.

These standards are up to date and are formulated keeping in mind different quality assurance standards. This would ensure that a quality product in the form of codes is delivered. With the implementation of these practices, it would be really easy for the data scientists to meet the requirements of their customers and deliver quality results.

Conclusion

Following a set of standard procedures can make the work of data scientists’ error-free to a great extent. Also, it enables easy quality checks ensuring good delivery of an end product.

 

Big Data Influences Online Trading in 3 Primary Ways!

Posted on by Imarticus Learning

Organizations and corporates are using analytics and data to get insights into the market trends to make decisions that will have a better impact on their business. The organization involved in healthcare, financial services, technology, and marketing are now increasingly using big data for a lot of their key projects.

Big Data influences online trading in 3 primary ways:

1. Levels the playing field to stabilize online trade

Big Data analytics

Algorithmic trading is the current trend in the financial world and machine learning helps computers to analyze at rapid speed.

The real-time picture that big data analytics provides gives the potential to improve investment opportunities for individuals and trading firms.

 

 

2. Estimation of outcomes and returns

Big Data AnalyticsAccess to big data helps to mitigate probable risks on online trading and making precise predictions.

Financial analytics helps to tie up principles that affect trends, pricing, and price behavior.

3. Improves machine learning and deliver accurate predictions

Big data analytics training can be used in combination with machine learning and this helps in making a decision based on logic than estimates and guesses.

Big Data Analytics

The data can be reviewed and applications can be developed to update information on a regular basis for making accurate predictions.

 

The Art of Machine Learning!

Posted on by Imarticus Learning

Machine learning is the application of Artificial Intelligence (AI) that enables systems to learn automatically and improve from experience without being programmed directly. Its main focus is on the development of programs that access data and use the same for self-improvement.

The machine learning process starts with observing data to look for similar patterns in any form and make better decisions in the future based on these trends. The main aim is to enable the computers to learn automatically and adjust actions accordingly without human intervention or assistance.

Data mining and predictive modeling involve similar processes as machine learning. Both these methods involve searching through data to look for patterns and then adjusting the program actions according to those patterns.

A common example of machine learning for people is shopping on the internet and being served ads related to it. This happens because online ad delivery is personalized almost in real-time by recommendation engines using machine learning.

Along with personalized marketing; detection of fraud, spam filtering, network security threat detection, predictive maintenance, and building news feeds are other common machine learning use cases.

Some machine learning methods
Machine learning algorithms are often categorized as supervised or unsupervised.

  • Supervised machine learning algorithms can apply past learnings to new data with the use of labeled examples to predict future events. It starts with the analysis of a known training dataset based on which the learning algorithm produces an inferred function to make predictions about the output values.Targets are provided by the system for any new input after sufficient training. The learning algorithm can also compare its output with the correct, intended output and find errors in order to modify the model accordingly.
  • Unsupervised machine learning algorithms – These types of algorithms are used when the information used to train is neither classified nor labeled. Unsupervised machine learning enables you to understand how systems can infer a function to describe a hidden structure from unlabeled data. The output given by the system is not right, but it explores the data and can draw conclusions from datasets to describe hidden structures from unlabeled data.
  • Semi-supervised machine learning algorithms have qualities of both supervised and unsupervised learning since they use both labeled and unlabeled data for training. Mostly, these algorithms use a small amount of labeled data and a large amount of unlabeled data. Learning accuracy is considerably improves in systems using this method.When the acquired labeled data requires skilled and relevant resources in order to train it or learn from it, semi-supervised machine learning is used. Otherwise, additional resources are generally not required for acquiring unlabeled data.
  • Reinforcement machine learning algorithms is a learning method that collaborated with its environment by delivering actions and finds errors or rewards. The most pertinent characteristics of reinforcement learning are trial and error search and delayed reward.Machines and software agents can automatically determine the ideal behavior within a particular context in order to maximize their performance using this method of machine learning. Simple reward feedback is required for the software specialist to learn which action is best and is known as the reinforcement signal.

Large quantities of data can be analyzed using machine learning. It identifies profitable opportunities or dangerous risks by delivering faster, more accurate results; however, it may also require additional time and resources to train it properly.

Large volumes of information can be processed more effectively if machine learning is combined with AI and cognitive technologies.

For example, Facebook’s News Feed customizes each user’s feed with the help of machine learning. If a user frequently likes or shows any activity on a particular friend’s posts, the News Feed will start to show more of that friend’s activity earlier in the user’s feed.

At the backend, the software is simply using statistical analysis and predictive analytics to identify patterns in the user’s data and use those patterns to populate his/her News Feed. If the user no longer shows interest to read, like, or comment on the friend’s posts, that new data will be included in the dataset and the News Feed will update accordingly.

The Role of AI in Minimising Physical Contact in Public Spaces!

Posted on by Imarticus Learning

The novel coronavirus pandemic has forced a majority of countries around the world to enforce lockdowns. Although met with initial resistance, a large chunk of the global population has stuck to social distancing and shelter-in-place norms, allowing the curve to be flattened.

As countries now begin to emerge out of lockdowns in phases, the focus will turn to maintain high standards of sanitation and hygiene. This is to avoid undoing the work that has been done over the past few months as well as set new norms for effective mitigation and disease controls. Amongst these, processes to minimize the frequent touching of common surfaces in public spaces will certainly feature.

So far, however, all efforts have been wholly dependent on manual efforts and individual dedication to social distancing and mitigation. AI can be pivotal in the efforts to curb the touching of surfaces in public areas without banking on individuals entirely.

Here’s how:

  • Contactless Access Systems

Tech titans are currently exploring the use of technologies for facial recognition to monitor the social distance between staff members. These can also be taken one step further to be combined with thermal scanning; when paired, this system can regulate who enters and exits the front doors in just a few seconds.

Machine Learning

This system also negates the need for touch-and-go biometric scanners or ID scanners which often become a collection point for employee throughout the day. Artificial Intelligence can be used to virtually cordon off some parts of the office as well as maintain control over how many times a person touches their face in a day (which is one of the quickest methods of COVID19 transmission).

  • Leveraging Voice Commands

Voice functionality has penetrated many aspects of human lives– and it’s only set to increase. Voice commands can be used to operate systems in public spaces such as bathrooms, elevators, entryways and cubicles to minimize the risk of contact. It can also be implemented at the water cooler, in the printing room and in office pantries, which are often places that see the highest footfall in large-scale organisations. Voice functionality can be implemented by integrated voice assistants and or smartphone apps. Aside from voice commands, gestures can also be used to minimizing the frequency of touching high-risk surfaces such as flushes, taps, door handles and elevator buttons.

  • Smart Handles and Locks

Doorknobs and handles are high-priority areas for sanitation teams given that we subconsciously handle them every day. AI can be implemented to reduce the need to physically touch handles to open doors. Technology can be used to kick into motion self-locking or gesture-controlled mechanisms. In a case where physical touch is absolutely required, AI can also be used to trigger the dispensing of antibacterial coatings or single-use sanitary sleeves. Newer inventions that use these technologies are able to be retrofitted onto existing doorknobs and handles, making them a quick fix to the sanitation problem in this aspect.

  • Location and Distance Tracking

Although some industries are slowly opening up, others have seen an influx of workers considered essential. However, that doesn’t reduce the need for strict social distancing measures, which is where AI comes into the picture. Artificial Intelligence can be used to account for the location of every employee in the facility and alert them if they have crossed social distancing boundaries.

Additionally, AI can also be used to demarcate spaces in queues and cubicles to maintain distance between employees. This system can be implemented through smartphone apps or wearable devices such as smartwatches.

Conclusion

Even after the pandemic loosens its hold, social distancing is slated to become the new norm. Businesses looking to leverage AI to maintain these rules without manual labour can consider upskilling their IT team through an artificial intelligence course or Machine learning training to ensure they’re achieving their potential.

The Increase in Data Science Education in India, Explained!

Posted on by Imarticus Learning

Data science jobs and related roles are increasingly becoming some of the most coveted jobs across industries. This is partly due to how the data science field can cut across industries to be of value, but also thanks to its resilience in tough times and the needs it has responded to.

Data ScienceOver the past few months, colleges and academic institutions have seen a significant rise in enrollment in data science courses in India. The choice is wide– potential students can choose from full-time, part-time or short and snappy online courses to either fill a gap in their skillset or experiment outside their comfort zones.

Although the potential for online learning had been realised by many even a few years ago, certain situations contributed to its exponential rise in recent times.

WFH and Remote Learning During the Coronavirus Pandemic

As lockdowns and shelter-in-place restrictions were imposed on countries all over the world, schools and colleges also had to pull down the shutters. Learning was taken online; in many institutions, exams and lessons were replaced by the opportunity to take online courses that otherwise wouldn’t have been accessible. Whether as a result of this or to fuel this trend, online education providers also reduced or waived off subscription fees and made certain courses available to all regardless of budget or geographies.

As a result, there was a surge in remote and online learning, not just from universities that students were enrolled in but also from coveted universities on the other side of the world. With the demand for data scientists expected to increase, professionals see new opportunities for growth. This, in turn, fueled the desire for upskilling and even pivoting careers as the economy slowed down.

Exposure to Global Universities and Opportunities

Online learning has made courses available in virtually any country from international universities and institutions. By making education accessible globally, online learning significantly increases the scope of the curricula as well as the teaching standards. Another benefit of this exposure is also the ability of graduates and professionals to connect with industry experts in other countries.

Data Science

Enrolling for data science courses in India that are offered by global universities is also a fantastic learning opportunity.

It exposes students to data science landscapes in other countries as well as lays bare the scope and possibilities they have well within their reach.

Once countries open up and travel restarts, students might also consider physically enrolling in these universities to explore topics further. Having a certificate or two in your portfolio indicates to the interviewer or the recruiter that you are interested and have done preliminary research which has only served to whet your appetite further.

Completely Online Courses

Until very recently, full-fledged online courses weren’t popular or even encouraged by governmental departments in India. Indian universities and colleges have not been permitted to deliver over 20 per cent of a degree online for several years. However, in the first move of its kind, the government gave the green signal for fully online courses in order to democratize education and erase barriers to learning caused by transport, accommodation and overall access.

The approach to fully online degrees is still cautious and restricted to particular subject areas. That said, it is still a welcome shift, especially for those looking to find data science jobs but lacking the access to opportunities that a lot of metropolitan cities and countries enjoy.

Conclusion

Online learning has significantly cut down barriers to entry that involve finance and access. It is a welcome step towards democratizing knowledge and making certain domains of the job market accessible to virtually anyone with a smartphone and a stable internet connection.

Seeing as data science jobs are set to increase in number, now is the ideal time for this surge in data science education, so that students are well-prepared for roles of the future.

5 Tips To Successfully Start a Data Science Job Remotely!

Posted on by Imarticus Learning

While the news of mass layoffs has inundated the market, certain industries continue to hire with one eye on the future. The data science realm is one such job market. Quite a lot about the recruitment and onboarding processes have changed; this makes transitioning into a new role a lot more complicated.

Keeping all this in mind, it is imperative that, as a candidate, you take things into their own hands. You can prepare an action plan to approach the first day of your remote data science career with enthusiasm– and this post will help you along the way.

Tip #1: Ask for A Preview of the Process

Proactively arm yourself with a blueprint of the onboarding process– this is especially relevant in current remote working scenarios. Depending on the job role you’ve been hired for, your onboarding process may be elaborate or short and snappy. Understanding what it will look like for you is a great way to avoid spreading yourself out too thin in the first few days or virtually walking in without a clue. It will also highlight any gaps you may need to fill in your skillset, in which case you might need to enrol in a data science course.

Tip #2: Reach Out to Your Teammates

It’s much harder than usual to connect with first-time teammates and colleagues in a virtual environment; however, since someone has to do it, it can be you. Not only will this allow you to establish your presence and role in the team, but it will also paint a favorable picture of you in times when first impressions are rather restricted to screens and voice calls. Try to gauge how best your team works, what communication tools they use and what they do outside of work. This personal rapport will go a long way.

Tip #3: Ensure You Have Continuous Access to Technology

Technology is the backbone of the remote working process– especially so for data science roles. Before your first day, it is a good idea to take stock of all the tools you have and how you can add to them if required. You can first start with hardware– laptops or desktops, sufficient working space, additional accessories– before moving on to software. If you find that you need something to perform your role, it is always advisable that you reach out to the onboarding team and see if they can help.

Tip #4: Be Forthcoming in Your Questions and Help

A virtual environment makes it significantly more difficult to read and react to facial or virtual clues. If you’re curious about something or don’t understand a task, it is best to be forthcoming about it. This tactic leaves no grey areas or causes for misunderstanding. Similarly, don’t hesitate to offer help where you feel like you have more to offer. This tip will make you a more valued member of your team as well as cement the skills and talents you bring to the table.

Tip #5: Weigh in Your Emotional Responses, Too

When starting a data science career remotely, it is easy to feel lonely and disconnected with your teammates despite working on the same projects. However, it is always recommended that you check in with yourself periodically and understand if you are adjusting. Reach out to colleagues to build a friendly rapport with them. Take time away from the computer and stick to strict work hours as much as possible so you don’t burn out.

Industries across the board have shifted operations to a work-from-home basis in order to cease the spread of COVID19. If you’ve been lucky enough to land a remote data science job, it’s best to head into it with a determined mind and an action plan in hand!