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Career opportunities in Data Science

by | Mar 30, 2021 | Uncategorized | 0 comments

What is Data Science

A scientific study  that deals with large volumes of data using modern tools and techniques to find particular patterns, and meaningful information, and thus make intelligent business decisions. Data science usually uses machine learning algorithms to build predictive models for its prediction.

Now that you know what is data science, let’s see why data science is essential in the current scenario.

When we Google  math requirements for data science, the three topics that come up are calculus, linear algebra, and statistics.

How Data Science is important

Data science constitutes better decision making.It also uses for following as well

  • Perform study on the data
  • Identify the real reason of a problem by asking questions
  •  Using algorithms  data modeling
  • Visualize the results via graphical tools

Typical example for prediction in daily life is

Weather: Predicting rains and forecast based on wind, temperature, latitude, day of the year factors.

Prerequisites for Learning Data Science

Here are some of the technical concepts you should know about before starting to learn what is data science.

1. Machine Learning

Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.

Machine learning and artificial intelligence share the same definition in the minds of many human but  there are some unique differences readers should know

Machine learning is considered as the backbone of data science. Data Scientists need to have a solid idea on Machine Learning  along with the basic knowledge of statistics.

https://www.greatlearning.in/great-lakes-artificial-intelligence-and-machine-learning?&utm_source=google&utm_medium=Search&utm_campaign=AIML_tier2_Purchase_Intent-Course_AIML_Combined&adgroup_id=105029248480&campaign_id=10280817009&keyword=%2Bstudy%20%2Bmachine%20%2Blearning&placement=&gclid=Cj0KCQjw9YWDBhDyARIsADt6sGYa519nTDVCGdP4KKxCkTGnBS83SxYOYBVgpjpLxmhs2WhaIn1jJZMaAkH_EALw_wcB

2. Modeling

Mathematical models enable you to make calculations and predictions based on your knowledge about the data. Modeling is also a part of Machine Learning and which helps to identify which algorithm is the most suitable to solve a given problem and how to train these models.

3. Statistics

Using statistics, we can gain deeper and more fine grained insights into how exactly our data is structured and based on that structure how we can optimally apply other data science techniques to get even more information. Today, we’re going to look at 5 basic statistics concepts that data scientists need to know and how they can be applied most effectively!

  • Statistical Features

    • Important analyses in descriptive statistics include normal distribution , central tendency , variability, variance, standard deviation, modality, skewness and kurtosis
  • Probability Distributions

    • Probability distribution is mathematical function which provide the possibilities of occurrence of various possible outcome that can occur in an experiment.There are many types of probability distribution 
      • Normal Distribution
      • Poison Distribution
      • Uniform Distribution
    • It is the technique for reducing the number of input variables in training data. When dealing with high dimensional data, it is often useful to reduce the dimensions by projecting the data to a lower dimensional subspace which captures the “essence” of the data.
    • Data sampling is a statistical analysis technique used to select, manipulate and analyze a representative subset of data points to identify patterns and trends in the larger data set being examined.You would get more information on sampling

4. Programming

Some level of programming is required to execute a successful data science project. The most common programming languages are Python, and R. Python. Python is the most widely used data science programming language in the world today. It is an open-source, easy-to-use language that has been around since the year 1991. … Natural data processing and data learning become a cakewalk with the packages contained in Python.

What are the programming languages used in data science please refer the below link

https://www.upgrad.com/blog/data-science-programming-languages/#:~:text=1.-,Python,around%20since%20the%20year%201991.&text=Natural%20data%20processing%20and%20data,the%20packages%20contained%20in%20Python.

5. Databases

A capable data scientist, you need to understand how databases work, how to manage them, and how to extract data from them.

https://analyticsindiamag.com/top-databases-used-in-machine-learning-projects/

Let us look at what are the basic skills a data scientist should possess
Data Scientist Skills:
  • Statistics.
  • At least one programming language proficiency – R/ Python.
  • Familiarity with Data Extraction and  Transformation
  • Machine Learning Algorithms.
  • Advanced Machine Learning
  • Big Data Processing Frameworks.
  • Data Visualization.

Data scientists help companies to solve their problems. Combining computer science, modeling, statistics, analytics, and math skills—along with sound business sense—data scientists uncover the answers to major questions that help organizations make objective decisions.

Difference Between Business Intelligence and Data Science

Business intelligence is a combination of the strategies and technologies used for the analysis of business data/information. Like data science, it can provide historical, current, and predictive views of business operations. But there are some key differences between these two.

Future job expectancy in data science

Jobs are expected to grow 16% from 2018 to 2028, which is much faster than the average for all occupations. Many companies are eager to hire skilled data scientists—organizations currently have difficulty filling these positions as the labor market for data scientists is highly competitive .

Range of Data Scientist salary 

Career opportunities in data have exponentially grown in the recent few years. Companies are eager to capture data and derive insights from it because of the technological advancements we are seeing. Accessibility of the data today can help to reap multiple benefits organizations from it. Because of this reason, companies are not shying away from offering increased data scientist salary in IndiaCompanies are throwing huge salaries at those having skills to take on the positions of Data Analysts, Scientists, Engineers, etc.

Executive summary

No doubt that the job opportunities and technologies in data science are increasing day by day. Youngsters who are searching for career opportunities in data science , here is your destination. Using data science human can do some advanced calculations using latest technologies thus can boost their business.

If you are looking for Data science courses please refer this link

https://analyticsindiamag.com/top-databases-used-in-machine-learning-projects/

https://www.greatlearning.in/great-lakes-pgpdsba?&utm_source=Google&utm_medium=Search&utm_campaign=DSBA_Tier2_Data_Science_Search_Course&adgroup_id=109135606740&campaign_id=11037060713&Keyword=%2Bdata%20%2Bscience%20%2Bcourse&placement=&utm_content=c&gclid=Cj0KCQjwmIuDBhDXARIsAFITC_6DtmA-PlNqnSK08i0h84aB2MlmT05oHaOv1yzmFXL7mUfureT0URcaAoS9EALw_wcB

If you are looking for career opportunities in Data Science please go through following link

https://ai-jobs.net/#s=1

https://www.analyticsjobs.co.uk/

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