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Presentation On Data Science Introduction

Home > PowerPoint Slides > Presentation On Data Science Introduction
Published in: Python Programming
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These are presentation slides I prepared for a lesson in introducing Computer Science beginners into the field of Data Science. You can learn all the foundations and ways data science is applied in our current world.

Joshua W / Dubai

4 years of teaching experience

Qualification: Bachelor's Degree

Teaches: Advanced Maths, Basic Computer, Coding & Programming, Robotics, Computer Science, Mathematics, Physics, Others

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  1. o Data Science in Python
  2. What is Data Science? Explosion of Data More data created in last 2 year than previous 200 years combined Multidisciplinary Intersection of Computer Science, Math and Domain Knowledge Making Sense of Data Take data and transform into meaningful insights Domain Expertise DATA Mathematics Computer Science
  3. • Mathematical calculations to data to derive meaning Mean, Median , Mode Standard Deviation, Variance , Skew • Distributions — Discrete/Continuous Statistics a 02 -40 683% 954% -30 -20 -10 10 20 30 40 Standard Deviations frorn Mean
  4. Probability • Calculate chances of something happening Flipping a coin Bayesian Probability - Posterior and Priors • Models to calculate probability P(BIA) P(A) P(AIB) =
  5. Machine Learning • Method of data analysis that automates analytical model building Artificial Neural Networks • Trial and Error with large datasets Draw insights and make predictions G)
  6. Data Visualisations Graphic representation of Data • Bar Charts, Pie Charts, Scatter Graphs , Line Graphs • Tableau, PowerBl Distributions — Discrete/Continuous GRANT LAND 2014-15 GOLDEN STATE WARRIORS
  7. Databases Storage of information in a structured way that is easy to write and read SQL queries — joins/ unions Relational databases • One to Many- Many to One, Primary Keys
  8. Data Science Processes Different people focused on different parts of process • Modes of collection, bias Data sanitization, sensitization • Plotting data, removing anomalies • Model fitting and Insights
  9. Python • Interpreted high-level general- purpose programming language. • One of most popular languages, growing popularity Easy to read English-like Syntax Performance issues • Extensive libraries
  10. Python in Data Science Open-Source language NumPy, Pandas,Requests • Tensorflow, Pytorch Pandas • Most commonly used by Data scientists • Most commonly asked for in TensorFlow job postings
  11. Web Scraping • Beautiful Soup library Parse the html of a website to extract relevant information Useful if data is required from a website you do not control • Money Savers Hackathon Project 9

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