What Are The Resources to Learn Data Science Online?

What is Data Science?
In the modern digital era, data is at the heart of every business that relies on the use of technological solutions to boost customer experience and increase revenue. The decision-making process has changed after the advent of data science. Businesses no longer work on assumption; they are using complex data analysis to obtain valuable insights about the market and consumers. So what exactly is data science and how does it work to further business objectives?

Well, data science can be simply explained as a discipline that deals with data collection, structuring and analysis. It involves the use of the scientific process and algorithms to obtain valuable insights from seemingly irrelevant pieces of information. Big data is at the centre of data science. Let’s delve deeper into why you should consider learning data science.

Why Learn Data Science?

The demand for data science professionals is ever increasing as more and more companies are deploying data science to obtain deeper insights.

Data Science Course OnlineThe demand for data science course online is also growing as more individuals are lured in towards the lucrative career prospects offered by this industry. There are numerous reasons to learn data science in the contemporary landscape.

The first and foremost is the outstanding remuneration offered to data science professionals. This is partly because data science is still in its nascent stage and there is a scarcity of trained professionals in this industry.

However, the demand for data science professionals by companies is on an upward trend.

 

In addition to this, the role played by data science professionals is very crucial for businesses as it involves analysing valuable company data to obtain insights and make predictions regarding the market.

Let’s explore how you can easily get trained for data science online.

Resources to Learn Data Science Online
Online learning is the new norm, the benefits of this method of learning is enormous. Moreover, the online courses are designed in such a way that it caters to specific training needs of individuals and there is no irrelevant content included in the courses. It is also feasible for people who are already working at a job and have limited time to learn a new subject. Here are a few resources that can help you learn data science online with ease and in a limited budget.

Google’s Machine Learning Crash Course

The machine learning technology is being extensively used by companies to cater to a growing audience base. Google’s Machine Learning Crash Course is designed for everyone; it doesn’t require you to have any prerequisite knowledge regarding the subject. Even people who have some knowledge in the field can opt for this course as it focuses on important concepts like loss functions, gradient descent, etc.

In addition to this, you will also learn about presenting algorithms from linear regression models to neural networks. The course learning materials include exercises, readings, and notebooks with actual code implementation using Tensorflow.

In addition to this crash course, you will also have access to a plethora of learning materials on data science and AI. These learning materials include courses, Practica, Guides and Glossary.

Imarticus Learning’s Data Science Prodegree

If you are looking to make a professional career in the field of data science then the data science course offered by Imarticus Learning is surely the best way to learn data science. The best thing about this course by Imarticus is that the knowledge partner for this course is KPMG.

This data science course takes a comprehensive approach towards learning data science and covers topics such as R, Python, SAS Programming, Data visualisation with Tableau, etc.

Data Science And Machine Learning Course with iHUB DivyaSampark @IIT Roorkee

Data science is a competitive field and to be successful you need to master the foundational concepts of data science. Imarticus Learning has created a 5-month data science program with iHUB DivyaSampark @IIT Roorkee. It will equip you with the most in-demand data science skills and knowledge that will help you to pursue a career as a data scientist, business analyst, data analyst and data manager. It features a 2-day campus immersion program at iHUB Divyasampark @IIT Roorkee and is delivered by top IIT faculty through live online training. Through this program, you will also get an opportunity to showcase your startup idea and get funding support.

In addition to this, the course trains individuals using industry sneak peeks, case studies and projects. The capstone projects allow individuals to work on real-world business problems in the guidance of expert project mentors. Upon the successful completion of this course, you will also receive a certification by Imarticus learning in association with Genpact. In addition to all this, you will receive interview preparation guidance and placement assistance.

 

3 Tips on Building a Successful Online Course in Data Science!

3 Tips on Building a Successful Online Course in Data Science!

The coronavirus pandemic is undoubtedly one of the biggest disruptors of lives and livelihoods this year. Thousands of businesses, shops and universities have been forced to shut down to curb the spread of the virus; as a result, massive numbers have turned to their home desks to work from and to tide over the crisis.

The pandemic has also influenced the surge of a new wave of interest in online courses. Over the past few months, many small and large-scale ed-tech companies have sprouted up, bombarding the masses with a wider range of choices than ever before. Many institutions have chosen to give out their courses at a minimal price and yet others for free. The format of these classes is different– hands-on, theoretical, philosophical, or interactive– but the ultimate goal is to take learning online and democratize it.

Naturally, it’s an opportune time to explore the idea of creating an online course– a data science online course, in particular, seeing as futuristic technologies will see a profound surge in attention come the next few years.

Here are a few tips to get the ball rolling on your first-ever online course in data science:

  • Create a Curriculum

Data science is a nuanced and complex field, so it won’t do to use the term in its entirety. It is important to think up what the scope of your course will be. You will need to identify what topics you will cover, what industry you want to target (if any), what tools you might need to talk about, and how best to deliver your course content to engage students.

education

General courses are ideal for beginners who don’t know the first thing about data science. This type, of course, could cover the scope of the term, the industries it’s used in as well as job opportunities and must-have skills for aspirants.

Technical courses can take one software and break it down– this is also a great space to encourage experiments and hands-on projects. Niche courses can deal with the use and advantage of data science within a particular industry, such as finance or healthcare.

  • Choose a Delivery Method

There are a plethora of ed-tech platforms to choose from, so make a list of what is most important to you, so you don’t get overwhelmed. Consider how interactive you can make it, through the use of:

  1. Live videos
  2. Video-on-demand
  3. Webinars
  4. Panels
  5. Expert speakers
  6. Flipped classroom
  7. Peer reviews
  8. Private mentorship
  9. Assessments
  10. Hackathons
    Education

The primary draw of online classrooms is also how flexible they are. Consider opting for a course style that allows students to learn at their own pace and time. Simultaneously, make use of the course styles listed above to foster a healthily competitive learning environment.

  • Seek Industry Partnerships

An excellent way to up the ante on your course and set it apart from regular platforms is to partner with an industry leader in your selected niche. This has many advantages– it lends credibility to your course, brings in a much-needed insider perspective and allows students to interact outside of strict course setups. Additionally, the branding of an industry leader on your certification is a testament to the value of your course; students are more likely to choose a course like yours if this certification is pivotal in their career.

EducationOther ways by which you can introduce an industry partnership include inviting company speakers, organising crash courses on industry software and even setting up placement interviews at these companies. The more you can help a student get their foot in the door, the higher the chances of them enrolling and recommending.

Conclusion
Building an online course in data science is no mean feat. However, it’s a great time to jump into the ed-tech and online learning industry, so get ready to impart your knowledge!

Why Does Data Ops For Data Science Project Matter?

What is Data Science?

Data plays a major role in every organization as it helps in making decisions based on facts, statistics, and trends. Data science helps to trace insights from the raw data generated, which in turn is used to make major business decisions. Implementing Data Science in business has several advantages.

  • It helps in reducing risks and identifying fraud models. Data scientists are trained to identify data that stands out in some way and they use methodologies to predict fraud models along with creating alerts every time unusual data is identified.
  • It helps organizations in identifying when and where the products best sell. This helps the organization to deliver the right products at the right time as per the customers’ needs.
  • It helps the sales and marketing teams to understand their audience well and helps with providing personalized customer experiences.

Why Data Science Needs DataOps?

Data scientists deal with searching for data, labeling, cleaning, and performing other tasks that consume a lot of time. Especially if the business has to maintain a backlog legacy, then the amount of data keeps multiplying every year. This is where the need for DataOps rises.

DataOps involves collaboration, automation, and continuous innovation to data within a data-driven environment. Just like software can not be expected to provide exact results outside its live environment, data projects may also tend to behave similarly and may have to be reworked completely to make it work in a production environment. It also has to be continuously monitored even after deployment. Which makes it even more necessary to implement DataOps in a Data Science project.

Data Ops for Data ScienceDataOps plays a major role in building best practices throughout a function. Through continuous production, DataOps helps organizations to deliver value to a range of stakeholders.

Another significance of using DataOps in Data Science is Automation. Data moves through a particular process within an organization. While Data is entered in one form, it does not exist in the same form. Data scientists have to build data pipelines, test, and change them before data is deployed.

Making use of DataOps best practices, you can get a constant stream of data flowing through the pipelines. Which in turn, helps to attain real-time insights from the data. This ensures to reduce the time taken in converting raw data into Valuable information.

Combining Machine Learning with DataOps helps in maintaining a continuous workflow through internal communication. With this, the data quality can be controlled through version control, constant development, and integration. Combining ML also improves the insights and has a great potential for extracting value from DataOps.

Introducing DataOps in the organization also means changes in the work process. It builds a new ecosystem with consistent communication between the departments. Employees of each department work together, in real-time, sharing a common goal.

Therefore, using DataOps in Data Science ensures to develop projects keeping in mind the business impact along with delivering it in a way that the management can understand.

Why Data Science Course?

The Data Science course covers a mix of topics like mathematics, Tools, Machine Learning techniques, Business Acumen, and several algorithms. The main principle behind Data Science is finding patterns from gigabytes of raw data collected.

In today’s competitive world, more and more organizations are opening up to big data, and the need for data scientists is also on the rise. They get exciting opportunities to work on and also get to come up with solutions for businesses.

What Does It Take To Be A Good Data Scientist?

What does a data scientist do?

The importance and applications of data science have grown exponentially over the past decade. Data science is still in its nascent stage and there’s a whole lot to be identified about this discipline. Businesses have started implanting strategic decision-making tools that leverage data science.

Data helps businesses by providing them with hidden insights and helps them predict the future outcome of their decision. This helps organizations to make a better business decision.

Let’s delve deeper into what these data scientists do and how it helps the organizations.

  • Finding a solution to business problems

Data ScienceOne of the most basic and key responsibilities of data scientists in an organization is to identify existing challenges and problems that a business is facing and finding solutions to remedy the situation. This might seem like a generic responsibility of every important professional but the main difference here is that data scientists use tons of relevant data to find the problem.

They try to come up with solutions after properly assessing the situation using various analytical tools that provide them with useful insights. They leverage statistical analysis, data visualization and mining techniques to provide effective solutions.

  • Find out relevant data using complex research

Data Science CareerThe 21st Century businesses are complex than ever, there are various factors that determine the fate of an organization. With the number of complexities that exist, it’s very difficult to figure out what impacts your business and how it does that.

Data scientists simplify this for organizations by studying all variables affecting a business. They use complex research work to identify the variables that have a maximum impact over the business and which are highly relevant.

  • Identify patterns and trends

Another important work of a data scientist that helps businesses is to identify patterns and trends. Data scientists use sophisticated data analysis techniques to find trends and patterns from the data sets at hand. These data sets are generally historical records of the organization. It helps them to identify the existing patterns and trends which is used to make predictions regarding the future movement of the variables.

How to become a data scientist?

Data Science CourseData science is one of the most in-demand skills in the industry and given the wide range of applications that it has, the demand for a data science professional will continue to rise in the future. One of the most common questions in the minds of data science aspirants is how to become a data scientist? There is no specific answer to this particular question. It depends on what stage of your career you are at and the skillset that you have.

A data science course by reputed institutions such as Imarticus Learning guarantees placement with top-notch firms in the industry in addition to providing relevant knowledge and skills. It also helps you provide guidance from the industry experts who are highly experienced in this domain.

Let’s delve deeper into some of the most prominent skills for data scientists that you should hone if you are planning to opt for a career in this field.

Analytical skills

One of the key skills that are required in this profession and that forms the base of all your work is your analytical skills. One should have an analytical mindset and should be able to identify trends and patterns from a big chunk of data. You should be able to assess a situation from a different perspective to reach a successful conclusion. One should be trained to work with software like Python and R and should be equipped enough to handle large volumes of data.

Problem-solving skills

Another important skill that you need to work on is your problem-solving skills. You need to use data to figure out challenges that exist in the business. After you have figured out the problems you will have to provide a solution using data analytics tools that will help the business to achieve its goals and objectives.

Where Data Science Will Be 5 years From Now?

Data is everywhere and data science is the perfect m mixture of algorithms, programming, deploying statistics, deductive reasoning, and data interference.

Data is the amalgamation of statistics, programming, mathematics, reasoning, and more importantly, a data scientist is a field that comprises everything that related to data cleaning, preparation, and analysis.

But when thinking about where data science will be 5 years from now, it’s useful to know how data science has made its unique position in the science field over the past five years.

Why is it hard to imagine a world without data?

As of late, advanced data have become so unavoidable and essential that we’ve nearly turned out to be unwilling to deal with anything that isn’t in data. To request that an information researcher takes a shot at something that isn’t digitized. Give them a table scribbled on a wrinkly bit of paper. Or then again, to more replicate the size of what we will discuss, whole libraries of thick books, flooding with tables of data.

Stack them around their work area and they’d most likely run away and never return. It is because the digital codes of information have become essentials and valuable. We cannot do modern work without them.  That’s the reason digitalization of the data is the whole story that makes our business work easier.

What data scientists do on a regular basis?

Data scientist begins their day by converting a business case into the algorithm, analytic agenda, develop codes, and exploring pattern to calculate which impact they will have on the business. They utilize business analytics to not just clarify what impact the information will have on an organization later on, however, can likewise help devise solutions that will assist the organization in moving forward.

So if you are perfect in statistics for data science, mathematics calculations, algorithms, and resolve highly complex business problems efficiently than the position of a data scientist is a round of clock available for you.

If we talk about data science salary, the job, and salary of the data scientist always on the top on in India but all over the world. A career in information particularly appeals to the youthful IT experts due to the positive relationship between the long periods of work experience and higher data science salary.

What does a data scientist actually need?

If you want to explore your career in data science, you are in the right place. Here we suggest you how to learn data science and statistics for data science along with the kind of skills recruiters expecting from you.

First and foremost, before entering in the data science choose the best data science online course. Because with the help of online courses you can build your skills easily and efficiently. Secondly, there are many roles in data science, so pick the one that depends on your background and work experience.

So, now you have decided on your job role and subscribed to the data science online course. The next thing you need to do is when you take up the course is learn data science go through actively, always follow the instructor instructions, the reason we are saying to follow the course regularly because it gives you a clear picture regarding data science skills.

The demand for data science is enormous and businesses are putting huge time and money into Data Scientists. So making the correct strides will prompt an exponential development. This guide gives tips that can kick you off and assist you in avoiding some expensive mistakes.

Data science is the core of the business because all the operations related to the business depend on the data science from statistics to decision making companies are using data science and its story not end here.

7 Reasons Owning Data Science Will Change Your Life!

Data Science is paving the way for a new future, but how much do we understand about the career of a data scientist? How much have we learnt about courses which help us learn data science? Or a data science salary?

Data Analytics is proving to be a complete breakthrough which is changing how industries work, and not just on a technological level, but on a very basic operational level too. In just a few years, it has emerged as the most incredible and lucrative career option. You might opt to learn data science, but you must know what it entails.

A data science program, even a data science online course mainly trains tech enthusiasts to process an immense amounts of jumbled up data extract information out of them, and to draw comprehensive information out of them.

From politics to retail to technology, data science is making companies equipped to cope with the access to data they have in the age of information technology. A data science salary is so high, mainly because with time it is emerging to be the strongest asset of companies. Amazon, Google, Microsoft and all the other corporate giants are spending millions of dollars to create a highly functioning data science team, and are even encouraging their employees to learn data science. Here’s why getting into data science will change your life.

Incredible career opportunities

Major tech giants have woken up to the truth that the smartest way to gather, process, understand and make a productive use of data in the age of IT is by having a strong data analytics team, with a specialized skill set. If you take a look at any leading job portals, you will see thousand of recruitment postings which are specifically looking for people who have undergone a data science program or even a data science online course. With the increasing demand of people in this field, it is no wonder that more and more young people are being driven to learn data science.

It’s all about big money

According to a survey by Indeed, an average data analyst earns something around $64,483 a year. And with the increased demand of data scientists in the corporate sector, young professionals will be able to negotiate a substantial hike in their salary, as the supply of good data analysts still remains low.

You can be choosy

If you do study data science you will be spoilt for choice when it comes to your field of interest, and eventually, when it comes to choosing a career, you can choose from titles like Big data engineer, Data analyst consultant, or an analytics specialist.

You’ll get to be irreplaceable

You must understand how lucrative the branch of data analytics is right now, and how much it is valued in the corporate market. As a data analyst or engineer you will be part of the most essential team in your company, and will be able to weigh in on the bigger operations and key assignments.

You might explore a new revenue source

One of the most fulfilling accomplishments is when you study data and interpret them to figure out a way for you company to make more profits, or cut some losses. In the age of IT, there are so many undiscovered options to raise revenues and ways to get more economical. You or your team can be responsible for this.

You might get to work in AI

Artificial intelligence is making use of data analytics now more than ever. Most tech enthusiasts aspire to work in AI someday. You must know that the data analytics boom has changed the face of AI completely, and it is becoming a bigger reality for the industries. More and more companies are focusing on AI and data science is making a huge difference in its operation.

A major priority

Did you know that 77% of successful companies around the world consider data analytics to be a crucial factor which affects their productivity? And as more and more companies wake up to the need for analytics, the competition and the market will only get better for anyone with a career in data science.