Data science

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This is just to help my people who wants to pursue their career as a Data Scientist. I strongly believe that 'We rise by lifting others'. I made this for one of my project work thought to share it here. Hope you guys will like it. Please feel free to suggest changes for better.

Données & analyses

Journey of a Data Scientist
Baby steps are the royal road to skill
By- Kartikay Dev Sharma

What is Data Science?
Data science is the field of study
that combines domain expertise,
programming skills, and
knowledge of mathematics and
statistics to extract meaningful
insights from data.

Why Data Science?
The purpose of Data Scientists
is to extract, pre-process and
analyze data.
-It's in demand.
-Abundance of Position
-A highly paid career
-Data Science is Versatile

Role of a Data
Scientist
They analyze, process, and
model data then interpret the
results to create actionable
plans for companies and
other organizations.

AI vs ML vs Data Science
Artificial intelligence is the ability that can be
imparted to computers which enables these
machines to understand data
Machine Learning is used in situations where we want
the machine to learn from the huge amounts of data we
give it. It is considered a sub-set of AI.
Data science covers the whole spectrum of data processing.
DS isn't limited to the algorithmic or statistical aspects.

Skills required
Statistics.
At least one programming language – R/ Python.
Data Extraction, Transformation, and Loading.
Data Wrangling and Data Exploration.
Machine Learning Algorithms.
Advanced Machine Learning (Deep Learning)
Big Data Processing Frameworks.
Data Visualization.

How to master
Programming in Python or R (either works)
Fluency with popular packages and workflows for
data science tasks in your language of choice. ...
Writing SQL queries.
Statistics knowledge and methods.
Basic machine learning and modeling skills.

Data Visualization
Data visualization is the graphical representation of
information and data. By using visual elements like charts,
graphs, and maps, data visualization tools

Data Cleaning
Data cleaning is the process of fixing or
removing incorrect, corrupted,
incorrectly formatted, duplicate, or
incomplete data within a dataset.

Data Manipulation
Data manipulation refers to the process of adjusting data
to make it organised and easier to read.

Salary
The median salary for an experienced data
scientist is $1628,000
The annual data science entry-level
salary is estimated to be $69,000.
The median salary for a mid-level
data scientist is $89,000.

Do you have any questions?
Mail it to me
sharmakartikaydev@gmail.com
All the best for your future journey of becoming
a Data Scienctist

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This project aims to predict whether a loan application will be approved or denied based on various factors such as applicant's income, credit score, loan amount, etc. Using a dataset containing historical loan application data, we employed machine learning algorithms to build a predictive model. The model was trained on features such as applicant's income, credit history, loan amount, loan term, and others. After training the model, we evaluated its performance using metrics like accuracy, precision, recall, and F1 score. The insights from this project can help financial institutions streamline their loan approval process and make informed decisions. Visit for more information: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/

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1. Journey of a Data Scientist Baby steps are the royal road to skill By- Kartikay Dev Sharma

2. What is Data Science? Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.

4. Why Data Science? The purpose of Data Scientists is to extract, pre-process and analyze data. -It's in demand. -Abundance of Position -A highly paid career -Data Science is Versatile

5. Role of a Data Scientist They analyze, process, and model data then interpret the results to create actionable plans for companies and other organizations.

6. AI vs ML vs Data Science Artificial intelligence is the ability that can be imparted to computers which enables these machines to understand data Machine Learning is used in situations where we want the machine to learn from the huge amounts of data we give it. It is considered a sub-set of AI. Data science covers the whole spectrum of data processing. DS isn't limited to the algorithmic or statistical aspects.

8. Skills required Statistics. At least one programming language – R/ Python. Data Extraction, Transformation, and Loading. Data Wrangling and Data Exploration. Machine Learning Algorithms. Advanced Machine Learning (Deep Learning) Big Data Processing Frameworks. Data Visualization.

9. How to master Programming in Python or R (either works) Fluency with popular packages and workflows for data science tasks in your language of choice. ... Writing SQL queries. Statistics knowledge and methods. Basic machine learning and modeling skills.

10. Tools to master

11. Data Visualization Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools

12. Data Cleaning Data cleaning is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset.

13. Data Manipulation Data manipulation refers to the process of adjusting data to make it organised and easier to read.

14.

15. Salary The median salary for an experienced data scientist is $1628,000 The annual data science entry-level salary is estimated to be $69,000. The median salary for a mid-level data scientist is $89,000.

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17. Do you have any questions? Mail it to me sharmakartikaydev@gmail.com All the best for your future journey of becoming a Data Scienctist

Data science

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