What Is Data Science & Why It Is A Smart Career Decision

Posted on August 6, 2025August 7, 2025 by Imarticus Learning

Introduction

Let me ask you a straightforward question: What if the decision of a new career, could land you right in the heart of a vast, global pool of innovation, high-paying job opportunities, and a game of limitless potentials? Tempting, right? That’s all Data Science in 2025. Regardless of whether you’re a new graduate, a working professional, or somebody looking to pivot your career, being asked what is data science could open doors to pathways previously unimagined.Firstly, in the last five years, Data Science has moved from a buzzword to an integral part of our everyday reality across many industries including: finance, healthcare, retail, and entertainment to name a few. By 2026 there will be over 11 million Data Science Job openings in India alone, therefore, it could be an incredibly smart and transformational career move.

Table of Contents

What is Data Science?
Careers in Data Science: Scope and Opportunities
How to Begin a Career in Data Science in India
Best Data Science Course with Placement Opportunities
Selecting the Best Data Science and AI Postgraduate Course
Why Data Science Is The Smartest Career Choice for 2025
Key Takeaways
FAQs
Conclusion

What is Data Science?

The world creates approximately 328 million terabytes of data on a daily basis. However, raw data itself is not useful unless we can interpret it. That’s precisely where Data Science helps. So, let’s dissect what is data science in easy words.

Data Science is an interdisciplinary field that uses -scientific methods, algorithms, and systems to extract knowledge & insights from structured & unstructured data. It uses mathematics, statistics, computer science, and other subject courses to make data actionable to the organization and have them use their intelligence to make better decisions.

Key Components of Data Science

Component	Description
Data Collection	Gathering raw information from multiple sources.
Data Cleaning	Removing errors, duplicates, and inconsistencies from data.
Data Analysis	Applying statistical methods to identify patterns and trends.
Machine Learning	Building predictive models that improve with more data.
Data Visualisation	Presenting findings in understandable formats like graphs.

In simple terms, Data Science is the process of extracting meaning from data to address actual problems.

Data Science Careers: Scope and Opportunities

It’s great to know what data science is, but to know where it can lead is more thrilling. The world has seen a rapid rise in careers related to data science, and hence, it’s one of the most future-proof and fulfilling career options today.

In India, organizations from all industries are hiring data professionals at a fast pace to remain competitive. Startups and mega players such as Infosys, TCS, Amazon, and Google – no one is leaving data teams behind.

Top Careers in Data Science

Data Scientist: The most desirable job, whose task is to develop models and draw out insights.
Data Analyst: Delivers on interpreting data that already exists to aid business decisions.
Machine Learning Engineer: Experts at creating AI-based solutions.
Data Engineer: Develops and sustains data infrastructure.
Business Intelligence Analyst: Converts data into strategic insights.
AI Engineer: Develops artificial intelligence technologies for implementation.
Big Data Engineer: Maintains and analyzes large-scale data sets.
Statistician: Implements statistical theories to address intricate problems.

With this diverse range of roles- jobs in data science have something for everyone, ranging from technical coders to business professionals.

How to Start a Career in Data Science in India

The question in everyone’s mind is – how to begin a data science career? The good news is, you don’t have to be a technical wizard to begin. But you do need to follow a systematic approach.

Here’s an Indian student and professional’s roadmap:

Step-by-Step Guide to Begin Your Data Science Career
Know the Basics: Learn what Data Science is.
Develop Technical Skills: Learn Python, R, SQL, and data visualisation software.
Mathematics & Statistics: Refresh probability, linear algebra, and stats.
Choose the Right Course: An MBA in Data Science with placement can speed up your career very much.
Work on Real Projects: Practical experience is priceless.
Build a Portfolio: Display your skills with GitHub, Kaggle, or personal projects.
Stay Updated: Be abreast of industry developments and trends.
Network and Apply: Go to meetups, LinkedIn networking, and apply for internships.

For those seeking a guided learning process, taking admission in a well-known data science course with placement is usually the best way to begin.

Top Data Science Course with Placement Options

If you’re serious about entering this industry, opting for a placement data science course is a big ticket. It provides you with not only technical skills but also job guarantee and industry exposure.

Best Courses to Make Career-Ready Data Scientists

Program Name	Features
Imarticus Learning – PG Program in Data Science and AI	Placement support, industry projects, AI integration
IIT Roorkee – Data Science and Machine Learning Certificate	Focus on advanced ML tools with placement assistance

For Indian students seeking best-of-breed training with job assurance, the Imarticus Learning Data Science and AI Program is one of the most reliable choices.

Selecting the Top Postgraduate Course in Data Science and AI

After deciding you want to venture into this area, the second step is finding the best postgraduate course in data science and AI. But with all the possibilities, how do you select?

A proper postgraduate course should have – industry-focused curriculum, practical projects, experience with AI technologies & career guidance. Considering how interdependent AI and Data Science are, studying both together maximizes your job opportunities.

Factors to Keep in Mind When Selecting a Program

Curriculum crafted by industry professionals.
Both Data Science and AI emphasis.
Hackathons and real-world projects.
Career services and placement assistance dedicated.
Flexible online or blended learning possibilities.
Good student feedback and sector standing.

The best postgrad program in data science and AI gives you both technical skills and the skills to solve business issues with data-driven solutions.

Why Data Science is the Smartest Career Move for 2025

Let’s be honest – technology is not going to slow down anytime soon, nor will the need for data experts. Adopting Data Science as your career choice in 2025 is equivalent to investing in a future-proof property.

The latest findings from Forbes indicate that Data Science and AI will be the driving forces in global job markets over the next decade. India, with its thriving digital economy, is amongst the prominent markets for this boom.

Why 2025 is the Ideal Time

Massive opportunities for data science careers in India and around the world.
Competitive pay and high job satisfaction.
Opportunity to work on state-of-the-art AI and ML projects.
Freedom to work across industries such as healthcare, finance, and e-commerce.
High impact and mentally stimulating work.
Global mobility and work-from-anywhere options.

The Future of Jobs Report of the World Economic Forum marks Data Science among the most emerging fields.. and therefore it is a wise career choice.

Key Takeaways

Data Science is transforming business decision-making.
Careers in data science are booming in India.
You can begin with a placement-oriented data science course.
Picking the right postgraduate course in data science and AI guarantees career-readiness.
2025 is the best time to make the transition into this line of work.

FAQs

1. What is data science and why is it so important?

Data Science is the process of extracting insights from data to answer real-world questions & that’s why it’s so important for companies to remain competitive.

2. What do data science careers require?

You require technical skills such as – Python, SQL, statistics, and machine learning, in addition to problem-solving and critical thinking skills.

3. How to begin a career in data science with no technical background?

Start with entry-level courses and build your technical skills step by step, particularly with a data science course with placement.

4. What is the best postgraduate data science and AI program?

Programs like Imarticus Learning’s PG Program are best known for industry focus, AI, and placement support.

5. Are data science careers just for engineers?

Not at all! There are professionals from mathematics, economics and business to those coming from non tech backgrounds who have transitioned successfully.

6. How much does a Data Scientist earn in India?

— Entry level salaried roles can earn you between 6-10 LPA, and with experience, you can earn 20 LPA or even more.

7. What industries hire Data Scientists?

IT , finance, healthcare, e-commerce and even government organisations.

8. Does Data Science have a future in India?

Yes. with India’s digital transformation, the demand for Data professionals, will be exponential.

9. Can I take a data science program online?

Yes! There are many providers like Imarticus Learning which have platforms that offer extensive programs with flexible learning options and placement support.

10. How long will it take to be job ready?

Working with a structured program, most learners can be job ready in 6-12 months.

Conclusion

There has never been a better time to step into Data Science! With so many people interested in data, it’s possible to dominate industries and even economies based on data. The rigorous the increase in demand, potential salaries, and job satisfaction represents one of the best long-term decisions in your career.

If you are starting from scratch, or simply want to transition to a new career in data, 2025 could represent the beginning of the smartest decision in your career with its leap into Data Science.

Ready to begin your journey? Join the Imarticus Learning PG Program in Data Science and AI today and get your career on track for success.

External References:

Is Data Science a Good Career Path for Freshers?

Posted on July 8, 2025July 8, 2025 by Imarticus Learning

Introduction: The Emergence of Data Science Careers

Data science is the refinery, and the new oil — in today’s digital-first environment, is data. It has the ability to reshape business decisions as it already influences and forecasts customer behavior or even optimises healthcare processes.

If you’re a fresher wondering about your career path, you might be probably asking: Is data science a good career for me?

The answer isn’t a simple yes or no — it depends on your interests, aptitude, and willingness to learn.

But one thing is clear — career opportunities in data science are not just growing; they are exploding.

Data science is one of the world’s top five most promising jobs, with year-over-year hiring growth at 37%, according to LinkedIn.

Here, you’ll learn in depth:

Why data science is perfect for freshers
What jobs you can look forward to
What skills will help you succeed
What courses are worth it
What the future holds

Let’s break down the data on data science.

What Is Data Science?

Data science bridges statistics, computer programming, and business acumen to extract useful insights from data.

Fundamentally, it’s about providing answers to practical questions using data:

What should our next product to launch should be?
Which marketing tactic generates the most ROI?
How can we foretell fraud beforehand?

Practical Uses of Data Science

Healthcare: Forecasting disease outbreaks
Finance: Identifying fraud and credit scoring
Retail: Recommendation engines and customer segmentation
Sports: Player analysis
Government: Policy effect and citizen services

If you’ve ever seen a “Recommended for You” product, that’s data science in action.

Why Data Science Is a Good Career for Freshers

Unlike other tech roles that need years of coding experience, data science welcomes freshers who can grasp concepts and learn quickly.

Here’s why it’s beginner-friendly:

✅ Structured Learning Paths

You can start from zero by learning from courses like the Postgraduate Program in Data Science and Analytics from Imarticus Learning, which offers a comprehensive course in Data Science and Analytics.

✅ Project-Based Learning

Most courses involve real-world projects — you graduate with evidence of work.

✅ High Demand, Low Entry Barrier

Your skillset and problem-solving skills matter more to employers than degrees.

✅ Salary Growth

Data science roles have some of the best entry-level pay rates in industries.

Career Opportunities in Data Science

No one pathway — the field provides varied career paths. Let’s discuss some jobs that you can apply for as a fresher.

Entry-Level Data Science Jobs

Data Analyst
Junior Data Scientist
Data Engineer (Trainee)
Business Intelligence Developer
Machine Learning Intern
AI Support Associate
Quantitative Research Analyst

These activities include:

Data cleaning
Making reports
Code writing in basic Python/SQL
Dashboards making
Assistance in developing models

These positions entail:

Role	Average Salary (INR/Year)
Junior Data Analyst	₹5.5 – ₹7 LPA
Data Science Intern	₹25,000 – ₹45,000/month
Business Analyst	₹6 – ₹9 LPA
ML Engineer (Fresher)	₹8 – ₹12 LPA

Source: Payscale, AmbitionBox

These figures vary depending on the location, course qualifications, and hands-on experience.

Skills Needed for Data Science

Let’s break down the skills you’ll need into 3 tiers.

Technical Skills

Programming: Python or R
Data Visualisation: Tableau, Power BI
Database Management: SQL
Machine Learning Basics
Data Cleaning and Preprocessing
Statistics & Probability

Business and Soft Skills

Analytical thinking
Communication
Curiosity and adaptability
Business acumen

Data Science Tools to Learn

Tool	Purpose	Level to Aim
Python	Scripting and ML	Intermediate
SQL	Querying data	Intermediate
Power BI	Visualisation	Beginner
Jupyter Notebook	Documentation and modelling	Beginner
Scikit-Learn	ML model building	Beginner

These tools are all taught in the Imarticus Learning Postgraduate Program in Data Science and Analytics.

A Unique Insight: The “Proof of Work” Era

Traditional degrees are being overtaken by “proof of skill.”

What does it mean?

Firms desire projects, not papers
A GitHub portfolio is stronger than a résumé
Hackathons and Kaggle competitions are the new recruitment grounds

In fact, as per a 2024 Coursera report, 55% of hiring managers indicated that they’d employ a fresher with project-based certification over a master’s degree candidate.

Career Development Path in Data Science

Data science provides one of the most rewarding and versatile career development paths.

Common Growth Path

Data Analyst (0–1 year)
Associate Data Scientist (1–3 years)
Senior Data Scientist (3–5 years)
Data Science Manager/Lead (5–8 years)
Chief Data Officer / Consultant (8+ years)

With each step, responsibility, project scope, and, of course — increased compensation.

The best thing? Progression is merit-based, not age-dependent.

Career Opportunities for Data Science Entry-Level

Let’s discuss numbers once more.

More than 70,000+ data analyst and scientist jobs posted on Indian job sites
The demand is international in the US, UK, Singapore, and the Middle East
BFSI, Healthcare, E-commerce, EdTech, and Logistics industries are hiring
India is anticipated to have over 11 million analytics jobs by 2026, as per India Brand Equity Foundation.

The Future of Data Science Careers

The future looks bright, with innovation occurring quickly.

What’s Coming:

AutoML: AI that builds models with little human intervention
Explainable AI: Models that explain why they made a choice
Data Privacy Engineering
Predictive Analytics in Finance
No-code Data Science Tools

Predictive analytics is a prime skill in finance and analytics roles — perfect for those who are into finance + data science.

Best Courses to Begin Your Journey

The Imarticus Postgraduate Program in Data Science and Analytics is created for the fresher to start his or her career in the industry.

Why It Is Special:

Teaches full-stack capabilities from Python to ML
Contains industry capstone projects
Provides job placement assistance
Trained by industry professionals
Suits any graduate from any stream

How Long to Get Job-Ready?

Average 4–6 months with:

10–12 hours of study each week
2–3 projects
1 ready GitHub portfolio
1 mock interview round

Need a roadmap? Here’s what your first 12 weeks could be like:

Week	Focus Area
1–2	Python Basics + Data Types
3–4	SQL + Data Cleaning
5–6	Statistics + EDA
7–8	Power BI/Tableau + Dashboards
9–10	Machine Learning Basics
11–12	Capstone Project + Interview Prep

FAQs: Is Data Science a Good Career for Freshers?

1. Is data science difficult to learn for non-tech students?

Not at all. Several students from commerce and humanities have made the switch successfully.

2. Which one is preferable: a certification or a master’s degree?

It depends on your intention. If you need to get employed quickly, a project-based certification is better.

3. Can data science be a remote job?

Yes. A lot of companies have remote positions in data science, particularly at the entry level.

4. Do I require a laptop with heavy specs?

Mid-range laptops (8GB RAM, SSD) are enough to start with.

5. What is the stability of this job?

Very stable. Provided you continue to enhance your skills, the industry always has room for you.

6. Will AI destroy data science jobs?

AI will transform how we work and not replace us. Human discretion in interpreting data is priceless.

7. Can I transition from BCom or BBA to data science?

Yes. Many top data scientists have a business background and employ predictive analytics in finance as a transition.

8. Which firms recruit freshers/ job prospects for data science beginners?

TCS, Accenture, Capgemini, Cognizant, Flipkart, and startups in India.

9. What’s the future salary scope?

With experience of 5+ years, professionals can have a salary of ₹25–35 LPA in best companies.

10. Do I have to learn advanced maths?

No. Maths and statistics of high school level will be enough to begin.

Conclusion

So, is data science good for freshers? Definitely.

With formal training, practice, and proper guidance, even individuals with no background in tech can enter this high-potential profession.

If you’re attracted by the paychecks, diversity of work, or pure demand — data science provides new entrants an advantage in a cutthroat job market.

Key Takeaways

Data science is an entry-level career with thousands of job openings and increasing demand.
Certifications and live projects are more important than your degree or experience.
Programs such as Imarticus’ PGP provide a systematized roadmap to becoming 4–6 months job-ready.

Ready to Launch Your Data Science Career?

Discover the Postgraduate Program in Data Science & Analytics by Imarticus Learning and join thousands of learners who’ve already made the transition.

Upskill today, build tomorrow’s career.

Why Should You Learn Python For Data Analytics and Artificial Intelligence?

Posted on February 23, 2022April 1, 2024 by Imarticus Learning

2022 has seen a huge increase in both the number of data science applicants and also future aspirants all around the world. In India alone, LinkedIn, the global job search leader, announced a 25% spike in data science professionals as compared to 2021, and that is a huge number by a number of standards.

But one of the most common questions that ponders the mind of data science aspirants most often is why they should learn Python to get an edge in this profession?

Thus if you are planning for a career in data analytics and artificial intelligence in the future, and too have this question in your mind, in this article, we will answer exactly that.

Let’s get started.

Why Is Python Important for Data Science?

At the present moment, there are more than 35 different programming languages that are actively used by developers and coders all around the world. But among all of these, Python is undeniably one of the most versatile and well equipped, especially in the field of data science.

The reason behind this is simple; if you take a look at some of the most common tasks that are executed by a data scientist on an everyday basis, starting from data extraction and ELT (Extraction, Loading, and Transformation) all of them require a solid knowledge of Python coding and operation.

Along with this, another important reason why Python is so often relied upon as the go-to programming language for data science professionals is the fact that it comes with a suite of different packages, starting from SciPy, NumPy and pandas, which make complicated and time-consuming tasks easier, more efficient and effortless.

For instance, Matplotlib, which is one of the leading Python packages, is often used by data science professionals when they want to include visualizations or any sort of graphics in their simulations.

If all of this is not enough good reason, as to why you should learn Python

To get an edge for your career in artificial intelligence, here are some of the biggest advantages of the standalone programming language in itself.

Advantages of Python

Easy to Learn

If you are a beginner at coding and you are looking for a programming language that is easy and fast to learn, then Python should be your choice.

The programming language has been around since the late 1980s and has thus undergone several developments and improvements in the last couple of years, which has made the current version extremely user and beginner friendly to learn and execute.

Since data science is such a fast-paced career, where developments are literally happening overnight, the need for a language that is easy and fast to learn is a no-brainer, thus making Python one of the most obvious choices.

Scalable

When you would have spent a considerable amount of time coding, one of the first things you will realize is the fact that Python as a programming language is immensely scalable. Compared to programming languages like Matlab and Stata, which are industry leaders in their own might, Python makes it very simple and straightforward for anyone to scale. The language comes inbuilt with a suite of features that allows you to have multiple approaches and perspectives to solve the same problem, along with having a wide range of flexibility to try out new things as and when they are developed.

The scalability aspect of Python is the second reason why companies prefer their data science professionals to know Python. Scalability is immensely important in both data science and artificial intelligence, mainly because of the fact that new discoveries are being made on the regular.

Conclusion

Thus, if you want to give your career in data science an edge, now is the time to start enrolling for an Artificial Intelligence Training that comes packed with a course in Python.

We offer analytics and artificial intelligence courses at our centers in Mumbai, Thane, Pune, Jaipur, Delhi, Gurgaon and Bangalore.

AI, Data Science, Machine Learning Terms You Need to Know in 2022!

Posted on February 19, 2022March 29, 2024 by Imarticus Learning

In the present paradigm of technical knowledge, it is imperative to be aware of certain concepts to survive and thrive. Whether you are pursuing a career in artificial intelligence (AI), have a cursory interest in data analytics, or simply wish to broaden your horizons, here are some artificial intelligence, data science, and machine learning terms you need to know in 2021. Read on…

Natural language processing:

Both humans and computational devices use their own modes of language to communicate and share ideas to the extent of imparting and debating on the information. The languages, however, are different in their basic forms and formats. Using natural language processing, or NLP, artificial intelligence can decipher many human languages to suit specific functions that may range from the academic study of linguistics to providing utility to hearing-impaired people.

Data warehouse:

A data warehouse, as the name suggests, contains a large ensemble of data pertaining to businesses and learnings from past successes and failures to provide better services. One who is not entirely proficient in data architecture may yet take the advantage of data warehouses to gather business analytics courses and make far better decisions. This method allows one to find new ways to process old data and change future iterations of that data with his/her actions.

Data journalism:

This is a mode of journalism that is slowly gaining greater prominence and is proving its necessity in combating the ever-growing trend of fake news. In this form of news reporting, one focuses on proving his/her assertions through the collection and presentation of reliable data. This may be done through human and/or AI collection and calculations. Soon, we may be able to have a collated base of data obtained through AI learning. This will make it very hard for individuals and/or groups to spread misinformation.

Deep learning:

This uses artificial intelligence to construct structures that mimic the human neural network – starting from simple problems to finding layers of hidden information. Meanwhile, it makes errors and learns from them with the program often ending up with a different solution than what was expected by its programmers and set parameters. Using this process, we can identify and solve possibly any real-world problem. The degree of human supervision in this process can be ascertained at various levels of this process.

Cybersecurity:

Both defenders and attackers of databases are getting smarter, escalating the never-ending battles between cybersecurity and hackers. Often, the strategies used by either group are similar to the point of being indistinguishable. Here, any large organization employs AI and/or deep learning to be one step ahead of the threats that plague them.

The above-mentioned terms are only the tip of the iceberg when it comes to talking about new technology-related topics. Hopefully, they have provided you with new avenues to look into as per your interests, or at least recapitulated some of the basic terminologies.

How Has Data Science Given Rise to Smart Logistics?

Posted on October 17, 2021March 21, 2024 by Imarticus Learning

How Has Data Science Given Rise to Smart Logistics?

Every day, billions of packages are delivered to customers by the logistics industry. At every supply chain node, a large quantity of data is generated. Customer data and delivery data are collected by the logistics firms every day. Data science plays a crucial role in supply chain management and many other logistics processes.

Businesses are relying on data science to reduce waste, forecast demand cycles, manage delivery routes, and many other processes. Young enthusiasts can learn data science to earn a lucrative job offer in the logistics industry. Read on to know how data science is affecting the logistics industry.

Autonomous vehicles for logistics

With the growing population, businesses have to cater to the growing needs of the customers. Also, e-commerce sites are growing in number that has generated more online customers. Delivery teams now have to cover remote areas for delivering the packages to customers. Even the top logistics companies in the world are facing driver shortages. It is why many experts are suggesting the use of autonomous vehicles for delivering packages. It may seem like a far-fetched thought but, autonomous vehicles are already available in the market.

AI and ML algorithms are used for designing better autonomous vehicles. As a data scientist, one should be familiar with AI and ML. If autonomous vehicles disrupt the services of traditional vehicles in the future, data scientists will be in huge demand. You can learn data science now to make your skillset futureproof and earn a lucrative job offer.

Smart warehouses

For storing different types of products, logistics firms need many warehouses. Some products need to be stored under specific temperatures. For example, meat products need to be stored in cold temperatures. The temperature requirements may differ from one product to another in a warehouse. With the help of data science and ML, smart warehouses can be created. Smart warehouses help you set automatic alarms for any temperature failure. All the products can be stored in ideal conditions with the least manual interruption. It will prevent the product damages that occur in warehouses.

Market forecasting with data science

Data science can help in analyzing customer data and better supply chain management. With data science, you can forecast market demands and supplies. Many times, warehouses have to bear a loss due to oversupply or undersupply. Data science can help in designing smart algorithms that can predict supply and demand trends. Logistics firms can track their supply following the demands of the customers.

Reverse logistics with data science

Data science algorithms can identify the geographic locations that are prone to return the products. Based on that, you could target geographic locations accordingly. Fewer customers will return your product and you can save the cost for reverse logistics. You can build a successful data scientist career if you can help businesses to slash operational costs.

How to learn data science for logistics?

An online data science course in India can help in learning industry practices. Imarticus Learning is a reliable EdTech platform that can help in learning data science for logistics. The PG Program in Data Analytics & ML offered by Imarticus can make you job-ready.

With an industry-designed curriculum, you can learn about the use cases of data science in the logistics industry. From logistic regression to programming languages, this course will cover them all.

Conclusion

The course offered by Imarticus will help you in learning via 25 real-life projects related to data science. A data science online course can help in kickstarting a data science career or getting a raise. Start learning data science for logistics now!

What Are The Resources to Learn Data Science Online?

Posted on October 8, 2021March 28, 2024 by Imarticus Learning

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.

The 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.

How an Artificial Intelligence and Data Science Work For an Online Conference?

Posted on August 30, 2021March 26, 2024 by Imarticus Learning

Artificial Intelligence and data science are the driving force behind most of the online conference tools available now. The more advanced the AI used, the better its experience is for the users. The advancement enables the user to have a more personalized and better quality video feed and experience.

Artificial intelligence and video conferencing

Already there is the option to replace and blur the background as per convenience. The use of Artificial Intelligence and data science in this arena is much more than that. Background manipulation is only the tip of the huge iceberg.

There are other features such as translation for those who are not familiar with the language spoken and it works either way when implemented properly. There is another possibility of transcribing the same to make it easier to understand.

The noise reduction in the background comes as another advantage where there could be distractions, especially when it is working from home scenarios.

All of these features make online conferencing more convenient and comfortable which is crucial at the moment. As work from home is becoming more normal than ever and online conferencing is the big ‘thing’ now, it needs all inputs from the Artificial Intelligence industry to make it simpler.

How data science comes into the picture?

Although Artificial Intelligence and data science sound similar, they are two sides of the same coin. While AI is the major force behind online conferencing, data science is no less important.

Data science comes in handy when the employee’s data needs to be analyzed. For eg, in order to find the ideal time for a conference, the log in log out time of the employees would be useful. By analyzing this data, a more appropriate time could be deduced where there is a possibility of maximum participation.

The chatbots powered by Artificial Intelligence could also need the backup of data science to implement it more effectively. It helps to communicate with multiple users at the same time and reduces the call time for both sides.

Amazon has implemented these chatbots and has found success with the same. The users have also expressed satisfaction when it comes to minor issues which do not usually need waiting in line to talk to customer care. This is a perfect example of AI and data science in use.

Learn Artificial Intelligence and data science

AI and data science are raising the bar with their advancements and specializations. Its popularity and demand are at an all-time high with numerous job opportunities in both fields.

People are queuing up to enroll in an Artificial Intelligence course at any cost. Specializing in this area is fruitful for the professionals and newcomers equally.

Starting a data science career may have been difficult in the past but it is a golden opportunity for all right now. Unlike Artificial Intelligence, data science is more beneficial for working professionals to maintain and advance in their careers. It helps them climb the corporate ladder a lot easier than ever. Moreover, there are multiple branches in data science that one can easily choose the most appropriate for their career.

Wrapping up

Though data science and Artificial Intelligence were present in various aspects of life, the pandemic has made it more familiar for the common man. Online conferences are only one such aspect but the one that has made the maximum impact on everyone. There was a time when such concepts were frowned upon but the increasing use of smartphones and the user-friendly approach of such technology has made it possible to make online conferencing a normal and ordinary household term.

Tableau: Accelerating Decision-making with the Power of Visual Analytics!

Posted on August 28, 2021March 22, 2024 by Imarticus Learning

Tableau is one of the most frequently used data analytics tools. It is used for data visualization where the data is represented in a pictorial or graphical form. The raw data is converted into an understandable format by Tableau which can be further used for data analytics.

Firms use Tableau to understand the data and to use data analytics for empowering their business. Tableau helps in decision-making via forecasting, analytics, risk assessment, etc.

Let us see more about Tableau and how it helps in decision making & data visualization.

Importance of Visual Analytics

Visual analytics is the analytical reasoning of data via interactive visual interfaces which in this case is Tableau. Visual analytics helps in understanding the data better, finding outliers in the dataset, discovering insights, etc.

You can identify new opportunities for your business if you are visualizing your data via a good platform like Tableau. The benefits of using Tableau for visual analytics are as follows:

Tableau has excellent visualization capabilities and it helps in converting unstructured data into absolute logical results that are interactive. It is far better and powerful than its equivalent tools available in the market.
The easy-to-use interface of Tableau provides data analysts to work faster and better. The drag-and-drop way of arranging unstructured data into diagrams and graphs makes it easier for beginners.Tableau is powerful and provides high performance of big data sets too. Beginners can easily complete Tableau training in less time and can get fluent in using it.
You can create a unified dashboard on Tableau where you can connect to multiple data sources. You can connect your dashboard with Hadoop, SAP, DB, etc., and can visualize data better.
There are a lot of Tableau users throughout the globe and one can find a helpful Tableau community on online forums. Tableau also provides a mobile application through which you can keep your visualized data at your fingertips.

How Tableau Accelerates Decision Making?

Tableau helps in visualizing and analyzing data. The structured data can be used for risk identification & management, increasing ROI, business forecasting, etc. You are well informed about your firm’s situation via data analytics and get to know about the upcoming market trends. You access the risk involved in any new opportunity via data analysis and then obtain it if is going to boost your business.

Data analysis introduces clarity in your organization with a data-driven approach to obtain business objectives. Decision-making is hugely impacted via the use of data visualization tools and you will stay ahead of other firms in the market.

One can easily create and share analytics reports to your employees via Tableau, giving a sense of clarity. You can also use customer data to provide better services to them in the future. One can complete Tableau training online to understand how to use it.

Conclusion

Tableau is a powerful data visualization tool that can boost your business with better market predictions & risk assessment. Recent innovations in data analysis due to AI & machine learning have taken data analysis to a next level. You can learn more about data analysis via analytics courses available online. Start using Tableau for your business now!

A Most Trending Career in the World is Data Science!

Posted on August 22, 2021July 11, 2022 by Imarticus Learning

A Most Trending Career in the World is Data Science!

Information researcher is moving everywhere. The interest for such researchers is colossal, more than the number of accessible competitors. A new report clarified that the interest for these researchers has expanded by over half since last year.

The buzz that information science has made all throughout the planet is great. The field of best Data Science courses in India can change your profession completely and move your vocation into the swearing field.

WHO CAN BE A DATA SCIENTIST?

The information researcher is the person who can perform a wide range of parts of information crunching yet not really be a specialist in any of them, which in short is named as a ‘handyman’.

The individual who needs to turn into an information researcher should have numerical abilities, measurable abilities, and programming abilities, and the necessities to have a definite comprehension of every one of them.

This individual additionally needs to have solid business information with the goal that he/she can go through business issues totally and can fabricate solid business methodologies for what’s to come.

Really at that time can you apply your abilities viably in the association in which you will be utilized.

TOP COMPANIES HIRING DATA SCIENTISTS:

Top organizations, just as new companies, are needing information researchers due to the huge measure of information streaming in the association’s data sets.

A lot of graduates are anticipating their vocations in the field of information science since it is one of the generously compensated positions or has a promising future.

However, they neglect to comprehend the way that affection for coding, numbers, and calculations is exceptionally vital for the ones who need to manage huge information. It isn’t some tea.

It is testing and intriguing simultaneously.

The top business concerns incorporate Flipkart, Amazon, and LinkedIn and the new companies incorporate Accenture, Heckyl, and DataWeave.

Why is Data Science a Good Career in 2021?

Posted on August 20, 2021March 26, 2024 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.

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.

A 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.

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.

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).

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.

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.

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.

They 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.

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.