2. • Why ?
– Growth of data (28%) vs growth of data analyst(5.7%)
• Applications
:Astronomy,Healthcare,automotive,Finance,Gaming,Agric
ulture
• Data scientist,Data Engineer,Visualization expert,ML
Engineer,ML scientist
3. Data Science
• Data science is an interdisciplinary field focused on extracting knowledge from data sets,
which are typically large , and applying the knowledge and actionable insights from data to
solve problems in a wide range of application domains.
• The field encompasses preparing data for analysis, formulating data science problems,
analyzing data, developing data-driven solutions, and presenting findings to inform high-level
decisions in a broad range of application domains.
• As such, it incorporates skills from computer science, statistics, information science,
mathematics, information visualization, data integration, graphic design, complex systems,
communication and business
5. Step by step procedure to learn data science
Data
science
Programming
language
Machine
learning
IDE
Web scraping
Math
Data
visualization
Data Analysis
Python,R,Java
Classification,Regression,Reinforce
ment, DL , Dimesionality
Reduction,Clustering
Pycharm,Jupyter,
Spyder
Beautiful
soup,Scrapy,URLLib
Statistics,Linear
Algebra, Differential
Calculus
Tableau,Power BI ,
MatPlotLib.GGplot,
Seaborn
Feature engineering
,Data wrangling,
EDA