Data Science

What are the most valuable skills for a data scientist?


Data Science is now being integrated with industries across all sectors. That’s why not only are the data scientists expected to have a broader set of skills, but the employers also expect more cohesive specialisation and collaboration. According to our study, we found out that the following skills were crucial for a data scientist’s role:

Thorough knowledge of Python, as 44% of the professionals use it the most Knowledge of Tableau, as 51%, of the data scientists use it Studio as an IDE And in-depth knowledge of Hadoop

What is the average salary of a data scientist?


A report by AIM had found out that the average salary for a data scientist in India is ₹12.7 lakh per annum in 2018. However, this trend has levelled off with the average analytics salary capped at ₹12.6 lakh per annum across all experience levels in 2019. In fact, Data Analytics professionals are currently benefitting from the big data wave with analytics professionals earning 26% higher than an average software engineer in India.

What are the top algorithms that every data scientist should have in his/her toolbox?

It is very crucial for the machine learning enthusiasts to know and understands the basic and important machine learning algorithms in order to keep themselves up-to-date with the current trends. For example, the top five most popular algorithms that all data scientists should know are:

Logistic Regression
K-Nearest Neighbours
Naive Bayes
Support Vector Machines
Random Forest

Are too many people training to become Data Scientists?


Many of the organisations, as well as professionals, are worried that the market is being flooded with too many data scientists, as most professionals from the software background are now rushing upskill. This is rather an unfair question, to be honest.

The term data science is being used rather loosely — from analysts to data visualisers — all are being termed as data scientists. If one goes by this erroneous definition, then yes, it will appear that there are far too many data scientists these days. But if we take into consideration the actual data — that there are as many as 97,000 job openings in the field of analytics and data science in India alone — then we can see that this sector is not saturated, but thriving.

How do you recruit data scientists?


There are numerous traditional as well as non-traditional ways of hiring data scientists. Some of the traditional routes are:

  • Job postings on website
  • Job posting on social media
  • References

But gone are those days. Employers have now realised that to attract the unique breed of data scientists, they need to use unusual avenues like:
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  • Following profiles on Github
  • Organising and participating in conferences
  • Tracking WhatsApp communities and groups
  • Organising and attending meetups
  • Creating hackathons

How to prepare for a data science interview?


Cracking any interview requires preparation and in the case of data science it is not restricted to performing well on the big day alone. An aspiring data scientist is expected to prepare across multiple fronts like:

  • Build a portfolio of projects and MOOCs
  • Network with peers and stay up-to-date with who’s who, follow trends
  • Learn about the position that you are applying for
  • Go through questions asked in previous interviews

Why data scientists need to be story-teller?


As data gets deeper and more complex, it becomes imperative to bring in simplicity in it. And storytelling makes it simple and more interesting, drawing interest from listeners and readers alike. Also, Stories provoke thought and bring out deeper insights.

Also, when data and analytics reveal great insights, an absence of narrative makes it hard to relate to the facts. And this is where data storytelling comes into the scenario — it takes data visualisation to a whole new level. With the help of real-life instances and experience, a data storyteller helps its audience understand better.

Why do data scientists need Math?


If you are a data science aspirant, you need a strong background in mathematics and basic knowledge of statistics. In the midst of the hype around data-driven decision making, the basics are somehow getting sidelined. The boom in data science requires an increase in executive statistics and maths skills. Some of the fundamental concepts expected from a business analyst are correlation, causation and how to statistically test hypothesis. Basic knowledge of linear algebra and calculus is definitely required. It may be hard to master them initially but given the time and practice with working, these areas will be familiar and comfortable to work on.

What is Data Scientist Course about?

 Certified Data scientist is designed to provide a right blend of all four facets of Data Science

These four facets form four pillars for the data science field. They are 1. Programing 2. Statistics 3. Machine Learning 4. Business Knowledge.
The course is mainly focussed on Python for core data science programming, it also includes R as necessary to enable professionals working in R.
Statistics are covered as required for a Data Scientist, you may find a detailed syllabus in syllabus tab.
Machine Learning is the main tool kit for Data Science in predicting classification or regression.
This course courses all popular ML algorithms as detailed in the syllabus tab.
This course allows candidates to obtain an in-depth knowledge by laying a strong foundation and covering all the latest data science topics.
The increasing demand curve for data science professionals to manage the large set of data in various organizations providing millions of job opportunities in global markets.
The knowledge gained through this course along with IABACâ„¢ certificate surely helps you to become a data science professional.

Why this course?


This course comes as a perfect package of required Data Science skills including programming , statistics and Machine Learning. If you aspire to be Data Science professionals, this course can immensely help you to reach your goal.
Data scientist – Course Objectives

After successful completion of this “Certified Data scientist” course, you should have

Gained a better knowledge of the entire Data Science project workflow.
Understand key concepts of statistics
Gained hands-on knowledge of popular Machine learning algorithms
In depth knowledge on Data Mining, Data forecasting, and Data Visualization.
Able to create business case for Data Science project
Deliver end to end data science project to customer

Advantages of learning course?


Data science is the hottest field in the market as on today. Be it a small company or an MNC, they need a Data scientist to manage their large pool of data.

High demand for data scientists with only a few qualified people to hire
High salaries, nearly twice of an average software engineer as per Glassdoor report
This course not only designed to enable you for new career opportunities but also allows you to apply the new-age skills in your current work and become valuable in your current role.
Be assured that you are entering the future of data science much earlier to grab those wonderful opportunities arising from this biggest need in the business world.

Who should choose Data Science Course?


This course “Certified Data scientist” is not restricted to any specific domain.

Fresh Graduates or students from any discipline can choose this course to obtain better job opportunities in this most demanding data science field
Working professionals looking to change their domain to data science field.
Highly recommended for those who are aspiring jobs that mainly revolves around data analytics and machine learning
Project managers aspiring to switch to manage Data Science projects