Naukri Learning > Executive Programs > Analytics & Data Science > Data Science > Kings corner stones

Data Science Courses, Certification & Training by Kings corner stones

  • Courses (1)

  • About

  • Why should you do?

  • Who should do?

  • Related Careers

What is Data Scientist?

Data Science is a detailed study of information flow from big amounts of data present in an organization’s repository. It is a blend of data inference, algorithm development, and technology, which altogether contribute to solving complex analytically problems. With the help of Data Science, organizations have been successful to obtain meaningful insights from unstructured and raw data. Modern day businesses require skilled, knowledgeable and certified data scientists and they have emerged as the highest-paid professionals in the IT industry, in the recent years. This has thereby led to a significant increase in the number of professionals taking up Data Science course.
The importance of Data Science can be understood with the fact that even online marketing and entertainment giants like Amazon and Netflix, respectively are largely dependent on it to get the consumer insights. These businesses use data mining and sorting to understand users’ interests, identify major customer segments, send messaging to different market audience, and what not! Demand for Data Science professionals across industries, from businesses to non-profit organizations to government institutions.

Types of data Science

# Data Analysis
# Information Engineering
# Machine Learning

Why Should You Choose Data Science Courses?

# Reasons why Data Science training has been topping the charts of professionals for the past few years include –
# Booming market for data scientists and analysts, where the demands have jumped by approximately 400% over the last 5 years, paving way for more employment opportunities
# Attractive remuneration packages for professional with niche skills | Draw attractive remuneration packages, ranging between Rs. 10-15 Lac at mid-level
# Job opportunities across different industries
# Contribution to decision-making in the company
# Better freelancing opportunities
# Have a potential to contribute to enormous business benefits
# Opportunity to work with top names of the business, like Google, Amazon, Deloitte, IBM, and Accenture, among others
# More jobs are anticipated by 2030, for role like reactive queries, research work, data engineering and data infrastructure, machine learning, full stack data science, and many others
# 3,00,000+ Data scientists would be required across industries by 2020, with an increase of 3400 positions every month.

Who can become a Data scientist/professional?

Software Developer

If you are a software developer and are interested to take up a career in Data Science, you would need to know how business challenges are solved, how data is crunched and how different algorithms work! You can leverage your software development skills and learn new skills relevant to data science business. If you are aware of data analysis tools and languages such as SQL, R, Python, SPSS and SAS, then it will be easier for you to cope up with the complications of Data Science. Besides, you would also need to learn about –
# Contingency tables, Chi squared tests, T-tests, Pearson correlation
# Different types of regression models and decision trees
# Neural networks, clustering algorithms, and expert systems
# Logic programming, linear programming, data parsing and data profiling
# Artificial intelligence and machine-learning algorithms
# Various metrics of model performance evaluation

Data Analyst

As a Data Analyst, you must be having an experience collecting, processing and applying statistical algorithms to structured data for better decision making, and that would certainly be very helpful if you wish to take a step ahead and become a data scientist. As a data science professional, you need to learn-
# Specialist fields like NLP, OCR and Computer Vision
# SQL databases and database querying languages like MySQL, Postgress, and MongoDB, etc.
# Programming languages like Python/R, C/C++ Java, Perl
# Big data platforms like Hadoop, Apache Spark, Hive & Pig
# Cloud tools like Amazon S3, GCP, Azure
# R and/or SAS languages
# Machine learning models like Regression, Boosted Trees Support Vector Machines (SVM), Nearest Neighbor (NN), etc.

Business Analyst

A business analyst is responsible to offer recommendations on process improvement, software and solution design, while data science involves algorithm development, data inference, and other technological processes. Shifting a career from being a business analyst to a data scientist is not that tricky as the person already has domain expertise and industry knowledge, however, certain skills are definitely needed to be learnt, such as –
# Basic understanding of SQL, NoSQL, MPP databases, and Hadoop
# Knowledge of algorithms such as recommendation engines, K Means Clustering, Linear and Logistic regression, Time series analysis, text analysis, decision trees, and NLP
# Knowledge of tools like Python, R, Django, D3j visualizations, Talend Open studio, and Splunk
# Cloud tools like Amazon S3, GCP, Azure
# R and/or SAS languages
# Machine learning models like Regression, Boosted Trees Support Vector Machines (SVM), Nearest Neighbor (NN), etc.

System/Database Administrators

System and Database Administrators are looking to boost their career with a switch to data scientist profile. With the requisite skills they can work within their own organization, as most companies are moving towards the use of data to make business decisions.

Popular Data Science Course Specializations

# R Programming
# Machine Learning
# Clinical Data Science
# Statistical Data Science
# Applied Data Science

Popular Data Science Courses

# Data Scientist Associate Certification
# IBM Certified Data Architect – Big Data
# Oracle Business Intelligence Foundation Suite 11g Certified Implementation Specialist
# SAS Certified Big Data Professional
# EMC Data Scientist - Advanced Analytics Specialist (EMCDS)
# Certification of Professional Achievement in Data Sciences
# Certification in Business Analytics
# Certificate in Analytics and Information Management
# Data Mining and Applications Graduate Certification
# Biomedical Data Science Graduate Certification

How to Choose the Right Data Science Course?

# Talk to people who have already taken the course and gather some reviews
# See if the course provides a foundational understanding of Data Science and Statistics
# Check if the course is certified
# See if the course fits your budget
# Use online training listing pages and apply filters to shortlist the best courses available for various tools and techniques

Popular Data Science Course Providers

# Eduonix
# Quickstart
# Simplilearn
# Intellipaat
# Nulearn
# upGrad
# Amity Online University
# Manipal Prolearn
Know More

Who should choose Data Science Course?

• Engineering/MBA/Commerce graduates
• IT/Banking/Finance professionals
• Data/IT Analysts
• Test/Software Engineers
• Business Intelligence Analysts

How to become a Data scientist/professional?

No Prior Knowledge

If you are person who loves playing with the numbers and have a familiarity with the basic concepts of Math and Statistics can become a Data Science professional. Here are some of the tips that can help you start a career in Data Science.
# Pursue internship with any Data Science firm
# Find good courses that teach Statistics, Probability, and Linear Algebra
# Have a knowledge of optimization
# Be aware of the basics of Natural Language Processing, Information Extraction, Computer Vision, Bioinformatics, Speech Processing etc.
# Take up any online Data Science course covering the basics

Basic Knowledge

A formal degree in Data Science will provide the required skills in statistics, computers and analysis techniques to process and analyze complex data sets. Most Data Science courses help the participants and make smart decisions based on their findings. To improve your basic knowledge on Data Science, you would need to -

Study Pattern Recognition and Machine Learning

# Develop a creative and analytical approach towards data sorting and processing
# Choose your area of interest from data mining, data cleaning or machine learning
# Learn about data structures, database design, data mining, etc.
# Take up any beginner Data Science course

Intermediate Knowledge

# Learn about distributed architecture, security applications, and applied systems analysis
# Learn Multivariable Calculus, Numerical Linear Algebra, Computational Linear Algebra, Matrix Algebra and Probability
# Explore Optimization, Information Theory and Decision Theory
# Setup and Learn to use tools like R and SQL
# Have a good command over programming languages like Python, MATLAB, Julia, C++, etc.
# Take up any relevant Data Science course

Advanced Knowledge

Most of the professionals at basic and intermediate levels focus on sharpening their technical skills but forget that they need to improve their management skills too if they want to grow in their career. To climb up the corporate ladder in Data Science, you should –
Take up a project management course or an MBA in Data Science
# Obtain any professional certification like SAS/SQL certified practitioner qualification, or on any specific software used by companies
# Try working for where you can manage databases, analyze data, or design the databases
# Learn Machine Learning, an integral element of Data Science and have an edge over the others


To learn Data Science, you would need to -
# Take up a Bachelor's degree in IT, Computer Science, Math, Physics, or equivalent
# Earn a Master's degree in Data Science or related field
# Gain work experience in your area of interest
A number of institutions offer degrees in Data Science and the specialization can be chosen according to the experience of the participant and their area of interest.
Know More

Career Outcomes

  • Data Science Career Path

    After the completion of a data science training course, candidates can find opportunities in one of the professional fields immediately or in the future:
    • Data Scientists
    • Lead Data Scientist
    • Product Analyst Manager
    • Director of Engineering

    Skills Required for Data Science Professionals
    An advanced certification is the key to remain more relevant and competitive in the market and have a well-paid career. However, you need to possess some skill sets, mandatory for having a career in Data Science, which include –
    # Knowledge of Python Coding, Hadoop, Hive, BigQuery, AWS, Spark, SQL Database/Coding, Apache Spark, among others
    # Working experience with Machine Learning, Multivariable Calculus & Linear Algebra
    # Ability to write codes and manage big data chunks
    # Hands-on experience with real-time data and cloud computing
    # Creativity
    # Good business acumen
    # Great communication skills
    # Ability to use automated tools and open source software
Know More

Related Career Options

Data Scientist

Data scientists are professionals who are responsible for extracting insights or knowledge from data (both structured and unstructured) in various for...

Know More

Data Analyst

Data analyst is someone whose focus of problem solving and analysis relates to types of data and relationships between data elements in an IT system. ...

Know More

Big Data Developer

Big data developers are proficient in core scripting languages and responsible for the actual coding or programming of big data applications. They dea...

Know More

Big Data Architect

A Big data architect is trained to describe the structure of a big data solution. He/she is responsible for planning next generation big data systems ...

Know More

Software Architect

A software architect is someone who makes high-level software designs and dictates technical standards encompassing platforms, standards and tools. It...

Know More

Refine Results

Course Level

Mode of learning

  1. Postgraduate Diploma in Artificial Intelligence

    Artificial intelligence (AI) is a field of computer science that enables computers and machines to perform tasks normally requiring human intelligence. Its many applications range from chess-playing robots and autonomous cars to speech, image, and language processing, robotic manufacturing, and surveillance systems. In the twenty-first century, AI has experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding. AI techniques have now become an essential part of the technology industry, helping to solve many challenging problems in computer science

    Enquire Now

    Internet of Things , IOT

    Brochure Course Provider
Show Courses in Table

7034+ Jobs

as per Naukri database

Top Recruiters

Browse Category

Buy Safely with
We support secure payment methods


While Naukri Learning services have helped many customers over the years, we do not guarantee any interview calls or assure any job offers with any of our services.
The services associated with Naukri Learning are only provided through the website You are advised to be cautious of calls/emails asking for payment from other web sites that claim to offer similar services under the name of We have no associates/agents other than the partner sites that have been specifically named on the homepage of the website We also recommend that you Security Guidelines and Terms and Conditions