CYBER MONDAY OFFER: Flat 40% Off with Free Self Learning Course | Use Coupon CYBERMONDAY40

- Data Science Blogs -

Learn Data Science - Get Certified & See an Advancement in Your Career



Introduction

Data scientists are involved with gathering data and converting it into a tractable form, making it tell its story, and presenting that story to others.” is the saying of Mike Loukides who is the Vice President of O'Reilly Media. 

According to the U.S. Bureau of Labour Statistics, there will be the creation of more than 11.5 million jobs in the Data Science field by 2026. 

 data science

Who is a data scientist and what all technical aspects are included in his work?

Data scientists are the professionals who carry greater expertise in unfolding the data and also in analyzing the large sets of structured as well as unstructured data. 

The major role of a data scientist involves the acquisition of intelligence to solve problems as he has studied the programming languages of computer science as well as facts inscribed in the statistics and even mathematical formulas to resolve greater queries in the coding field.

Tasks of Data Scientists- Data scientists work on three pillars such as collecting, analyzing large sets of structured and unstructured data to yield actionable plans for enhancing the commercial growth of the company as well as small-sized organizations.

Reasons why Data Scientists are called as the analytical experts

Reasons why Data Scientists are called as the analytical experts

 Data Scientists

They are often labeled as the analytical experts who can easily utilize their skills in technology as well as find social science measures to search for the latest trends that help manage the data. 

Technical Knowledge

  1. Solve Problems- These professionals are known for their wide knowledge, contextual understanding, skepticism of the current assumptions to unmask the solutions to solve hidden business challenges.
  2. Fully Understand Coding - Data scientists are those set of professionals who fully understand the length and breadth of the coding spectrum in the field of computer science
  3. Updated Skills - Their technical skills are highly updated as they are able to create projects, websites, landing pages by performing the machine learning techniques that include python, Java C++, and much more.
  4. Strong Visualisation - A data scientist is also able to visualize the structured as well as unstructured data and can even create business reports. He carries a sharp eye for carrying out the analysis of risks and before the losses do happen to the company, his compiled set of risk reports are enough to project the losses that can fall in the path of the company’s growth.

Know the exact work of the data scientist

Extraction of Data

  1. Data Mining - The data scientist is also known for extracting the data in the form of information from numerous web servers and then imports them in the specific databases by the channels of mining the data. 
  2. Efficient cloud computing skills - He is also capable of performing research on big-data platforms as well as in computing the cloud tools such as Amazon Web Server and also efficiently structures the data warehouses. 

Data Science Training - Using R and Python

  • Detailed Coverage
  • Best-in-class Content
  • Prepared by Industry leaders
  • Latest Technology Covered

Hardcore Computer Engineering Skills

  1. Perfect Engineering Skills - The data scientist's software engineering skills are said to be very sharp because he not only understands the concepts about coding but also runs computer programming made projects on different servers
  2. Comprehends Technical Aspects - He also understands the technical concepts of Content Delivery Network and thus his help proves to be quite fruitful to the organization in running the audio-visual business scripts in the areas where data centers are not found in higher capacity.

Thorough understanding of Data Science Tools 

  1. Business Analyst Tools - A data scientist is someone who is already thorough with various concepts about business analytics and fully understands their usage and concept and perhaps this is the reason why many of them prefer to use tools like R, Big Data, Hadoop, and Spark. 
  2. Technical Experts - Data scientists are also classified as the experts who understand the life cycle probability, analytics project lifecycle and are also known for having the information linked to the life cycle of the IT product and also in analyzing the project. 

A data scientist is said to be someone who carries greater expertise in understanding variables and in measuring the central tendency.  With the severe impact of advanced data analytics to computing data statistics, one can easily summarise the data that is being run on numerous other platforms.

Know the exact objectives for learning online Data Science training

  • Accessible Data Courses - One Of the main objectives to learn data science is that they offer plenty of data science courses and help one to grasp the skills revolving around R programming, Python, Data Mining, machine learning with R, Data mining and live coding with real industry experts. 
  • Advanced Technical Skills - The learning of advanced technical skills are quite helpful in delivering a unified and comprehensive training that often teaches web-developers to cope-up with advanced concepts, skills of data science analysis. By learning these skills they can resolve technical queries. 
  • Helps Organizations - To Survive The training to learn data science online offers rigorous ways of how one can handle any type of structured data that is used to build the complex business setup and also by applying intuition and intelligence to it. In other words, it would surely retract meaningful conclusions that could further help organizations to create significant decisions over the targeted audience.
  • Helpful in Creating Complex Predictive Models - Its main objective is to provide every basic detail to learners and includes advanced learning too. It begins by introducing the person with the right usage of tools to frame the algorithms and complex predictive models to analyze the data and gain insights from it.   
  • In-depth Data Science Learning - It's the main objective also lies in creating the roadmap related to data science training and also allows one to enroll for free in learning in-depth data science training. It also gives a clear view of what has been expected throughout their training course over data science.
  • Offers Clarity - It offers clarity to the audience in using concepts like R and Python. 

Thus the major aim of learning data science online lies in the fact that it offers consistent growth. Whereas data-backed industries are capable enough of imparting the technical and sound knowledge about this particular field to aspiring individuals. 

Moreover, within a few years, they could surely gain the master of their machine learning skills. 

Question- Why to learn the data science models?

  • Avail Jobs in Non - IT Sectors-The courses of data science help an individual to get standalone jobs and that is the best part of learning them. Moreover, these roles are available in the non-core IT industries too. It means that with limited learning one could easily expand his/her horizons.  
  • Proper Understanding of Programming Languages - The courses of data science also allow the data scientist to utilize statistical computer programming languages like R, Python, SQL, and much more to manipulate and transfer data into meaningful insights.
  • Enables Web Developer to Create Models -
    • Data science models allow the engineers to develop the complex predictive models by using techniques like data analysis, cleansing, ingestion, visualization, mapping as well as drawing of conclusions.
    • The data science training enables web-developers to create models by using machine learning programming like clustering and decision tree learning as well as data learning algorithms that offer a different input about using the neural networks
    • Learning data science models help web-developers to represent the information by efficiently using the data visualization tools and techniques.

Question- What are the roles and responsibilities of the data scientists?

The major responsibility of the data scientist developer includes the building of algorithms and in designing the experiments that could be merged with existing data. It also includes analysis of the particular data which is used for pulling the business reports for the clients, colleagues as well as for the business purposes too.

  • To Manage Databases - His/her job role includes developing, managing as well as the use of relational and NoSQL databases. 
  • Efficient Use of Data Processing Tools - The role of the data scientist also includes the efficient use of big-data processing tools like Hadoop, Spark, MapReduce, Hive, and much more.
  • Efficient Understanding of Data Mining Methods - He /she can also select and deploy the data mining methods which are related to the needs of the project.
  • Enable one to enhance Data Collection - Many data scientists are also able to enhance the data collection by including what all things are relevant for architecting the analytics systems.
  • Helpful in Procuring Data - These tools also help a data scientist to procure, analyze, and standardize the huge data in a particular digital format that includes sales inventory, general ledger, and much more. 
  • Implementation of Statistical Techniques - A data scientist can easily manage and implement statistical techniques such as regression analysis, statistical tests, and much more.
  • Meeting with the Product Development Team - The role of data scientist also includes collaboration with the product development and engineering team.
  • Upgrading Business - A data scientists can also help the company to upgrade its business strategies by using the prevalent technologies, methods, and processes too.  

A data scientist is someone who could easily take the position as a technical thought leader and bridge the communication gap between the analytics and web team.

Data Science Training - Using R and Python

  • Personalized Free Consultation
  • Access to Our Learning Management System
  • Access to Our Course Curriculum
  • Be a Part of Our Free Demo Class

Question-What are the skills required to become the data scientist

Technical Skills

  • Python Coding- Python is regarded as the most common coding language that is typically seen in analyzing the data scientist role, a data scientist should have thorough knowledge about Java, Perl, C/C++.
  • Hadoop Platform- A data scientist is expected to be a professional who carries greater expertise to use the cloud computing and behavior-driven models such as agile scrum method. 
  • SQL Database Coding- A data scientist is someone from whom everybody expects to seek the solution to arising problems of SQL queries.
  • Machine Learning and AI- A data scientist is someone who is known for having in-depth knowledge about artificial intelligence and understands how decision tree models work.
  • Data Visualization- A data scientist is also an experienced individual who knows about the various ways of visualizing the unstructured data.

 

Non-Technical  Skills

  • Communication- A data scientist also happens to be a great communicator because he needs to be persuasive while using the data visualization tools in adding the graphic appeal and also for the easy absorption by all the teams of the organization.
  • Data-Driven Decision Making- A data scientist is someone who does not emphasize the final output without deciding, judging, and analyzing the information inscribed in the data sets.
  • Mathematical and Statistical Acumen- A data scientist is someone who couldn't reach heights if he doesn't understand the different types of tests that are needed to be performed for interpreting the analysis of databases.
  • Inner-Curiosity to learn new things- A data scientist is someone ready to learn a new set of things and can think of different ways of solving the queries within a limited time frame.

 

Know the Exact Salary of the data scientist and also know the different career paths

  1. Data Scientist - The estimated salary of a data scientist can go beyond USD 1,00,000 . It is the best because it allows a data scientist to analyze, create algorithms,  administer the databases and work on different decision tree models.
  2. Data Analyst - The overall salary of the data analyst ranges from USD 70,500 to USD 87,900. It is one such profession where he needs to interpret and analyze the growth and decline of the business in every fiscal year.
  3. Data Engineers - The salary of a data engineer is estimated to be around USD 89,700 and it is a high profile job because as a data engineer. A data engineer’s work is to create various regression models on decision trees and SDLC models too.
  4. Database Admin/Administrator - The overall salary of the database administrator lies in the range between USD 83,400 and USSD 94,300 and this job role includes administering the databases according to the information granted by the clients. 
  5. Machine Learning Engineer - The overall salary of the machine learning engineer is expected to go beyond USD 1,20,000 because he is an expert in creating AI models and fully understands their functioning. He also has full-fledged knowledge about machine learning programs such as python, Java C++, and cloud computing systems too. 
  6. Data Architect - The estimated salary of a data architect is near around USD76,800 and his major task is to structure the unstructured data by resolving the SQL queries and in building the base of software architecture. 
  7. App Architect - The estimated salary of an app architect is expected to lie near around USD83,500. An app architect is the professional who can design regression models by using the new set of technologies that work as the perfect way to run them on android systems.
  8. Business Analyst - The overall estimated salary of the business analyst is expected to near around USD76,500 because his main work includes developing the business reports as well as in expanding the business horizons
  9. Data and Analytics Manager - The overall salary of the data and analytics manager is near around USD85,760 and his major work includes analyzing and managing the data according to the standardized norms. 
  10. Business Intelligence  Developer - The overall estimated salary of the business intelligence developer is lying between USD 65,600 to USD 76,800. He is said to be the leading man of the organization because he is capable of creating new leads and can also convert them. 

Question-How to learn data science Online?

The certification courses linked to the data sciences are many not one. The main aim of these courses is to introduce a new wave of logical thinking in the minds of aspiring individuals who are capable enough of imbibing a new set of skills that involves working upon agile methods in the blends with machine learning programs.

Know the nine best certification programs in data sciences

Certified courses in data sciences aren’t only enough in letting one grab the golden opportunity to work with the best IT giants in the world like Apple Inc, IBM, HCL, Microsoft and HP but also offer them a sharp rise in their salary. These certified courses do help professionals to secure their position in the corporate world where insecurities of losing the jobs prevail more. 

  1. Dell EMC Proven Professional Certification Program
  2. Certified Analytics Professional
  3. SAS Academy for Data Science
  4. Microsoft Certified Solutions Expert (MCSE)
  5. Cloudera Certified Associate (CCA)
  6.  Cloudera Certified Professional: CCP Data Engineer
  7. Data Science Certificate – Harvard Extension School
  8. Amazon AWS Big Data Certification
  9. Oracle Certified Business Intelligence

Moreover, one can learn data science with python by enrolling in the certification courses and even get a free demo. With the help of real-life industry experts one can understand the grassroots of the technical concept that would reap many benefits to him and can add much more success to him.

So this was it, ‘why should you learn Data Science and How should you learn Data Science’. Hope you had a great time reading this blog. Write to us in the comment section below what your views are on the same.


    Janbask Training

    A dynamic, highly professional, and a global online training course provider committed to propelling the next generation of technology learners with a whole new way of training experience.


Comments

Trending Courses

AWS

  • AWS & Fundamentals of Linux
  • Amazon Simple Storage Service
  • Elastic Compute Cloud
  • Databases Overview & Amazon Route 53

Upcoming Class

2 days 04 Dec 2020

DevOps

  • Intro to DevOps
  • GIT and Maven
  • Jenkins & Ansible
  • Docker and Cloud Computing

Upcoming Class

10 days 12 Dec 2020

Data Science

  • Data Science Introduction
  • Hadoop and Spark Overview
  • Python & Intro to R Programming
  • Machine Learning

Upcoming Class

7 days 09 Dec 2020

Hadoop

  • Architecture, HDFS & MapReduce
  • Unix Shell & Apache Pig Installation
  • HIVE Installation & User-Defined Functions
  • SQOOP & Hbase Installation

Upcoming Class

9 days 11 Dec 2020

Salesforce

  • Salesforce Configuration Introduction
  • Security & Automation Process
  • Sales & Service Cloud
  • Apex Programming, SOQL & SOSL

Upcoming Class

2 days 04 Dec 2020

QA

  • Introduction and Software Testing
  • Software Test Life Cycle
  • Automation Testing and API Testing
  • Selenium framework development using Testing

Upcoming Class

3 days 05 Dec 2020

Business Analyst

  • BA & Stakeholders Overview
  • BPMN, Requirement Elicitation
  • BA Tools & Design Documents
  • Enterprise Analysis, Agile & Scrum

Upcoming Class

2 days 04 Dec 2020

MS SQL Server

  • Introduction & Database Query
  • Programming, Indexes & System Functions
  • SSIS Package Development Procedures
  • SSRS Report Design

Upcoming Class

2 days 04 Dec 2020

Python

  • Features of Python
  • Python Editors and IDEs
  • Data types and Variables
  • Python File Operation

Upcoming Class

-1 day 01 Dec 2020

Artificial Intelligence

  • Components of AI
  • Categories of Machine Learning
  • Recurrent Neural Networks
  • Recurrent Neural Networks

Upcoming Class

3 days 05 Dec 2020

Machine Learning

  • Introduction to Machine Learning & Python
  • Machine Learning: Supervised Learning
  • Machine Learning: Unsupervised Learning

Upcoming Class

18 days 20 Dec 2020

Tableau

  • Introduction to Tableau Desktop
  • Data Transformation Methods
  • Configuring tableau server
  • Integration with R & Hadoop

Upcoming Class

17 days 19 Dec 2020

Search Posts

Reset

Receive Latest Materials and Offers on Data Science Course

Interviews