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Data Science 101: Methodology, Python, and Essential Math
Data Science 101: Methodology, Python, and Essential Math

Data Science 101: Methodology, Python, and Essential Math: A beginner's guide to data science, starting from data science methodology to an introduction to data science in Python, to essential math for data science.

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Profile Icon Ermin Dedic
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$19.99 per month
Full star icon Full star icon Full star icon Full star icon Empty star icon 4 (2 Ratings)
Video Apr 2022 14hrs 49mins 1st Edition
Video
$9.99 $54.99
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Renews at $19.99p/m
Arrow left icon
Profile Icon Ermin Dedic
Arrow right icon
$19.99 per month
Full star icon Full star icon Full star icon Full star icon Empty star icon 4 (2 Ratings)
Video Apr 2022 14hrs 49mins 1st Edition
Video
$9.99 $54.99
Subscription
Free Trial
Renews at $19.99p/m
Video
$9.99 $54.99
Subscription
Free Trial
Renews at $19.99p/m

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Key benefits

  • Explain data science methodology, starting with business understanding and ending at deployment
  • Identify the various elements of ML and NLP involved in building a simple chatbot
  • Indicate how to create and work with variables, data structures, looping structures, and more

Description

The opening part of Data Science 101 examines some frequently asked questions. Following that, we will explore data science methodology with a case study. You will see the typical data science steps and techniques utilized by data professionals. Next, you will build a simple chatbot so you can get a clear sense of what is involved. The next part is an introduction to data science in Python. You will have an opportunity to master Python for data science as each section is followed by an assignment to practice your skills. By the end of the section, you will understand Python fundamentals, decision and looping structures, Python functions, how to work with nested data, and list comprehension. Finally, we will wrap up the two most popular libraries for data science—NumPy and Pandas. The last part delves into essential math for data science. You will get the hang of linear algebra along with probability and statistics. Our goal for the linear algebra part is to introduce all necessary concepts and intuition for an in-depth understanding of an often-utilized technique for data fitting called least squares. We will spend a lot of time on probability, both classical and Bayesian, as reasoning about problems is a much more difficult aspect than simply running statistics. By the end of this course, you will understand data science methodology and how to use essential math in your real projects. All resources are available at https://github.com/PacktPublishing/Data-Science-101-Methodology-Python-and-Essential-Math

Who is this book for?

This course is designed for people who are new to data science or who are interested in pursuing a career in data science, as well as those who wish to obtain a broad overview before diving into specialized data science topics. This course will also benefit students who want to master the fundamental arithmetic for data science or obtain an introduction to data science in Python. You need not have any prior experience in data science to take up this course.

What you will learn

  • Examine frequent questions asked by passionate learners
  • Explore data science methodology with a healthcare insurance case study
  • Solve a system of linear equations
  • Define the idea of a vector space
  • Recognize the proper probability model for your use case
  • Compute a least-squares solution through pseudoinverse

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 28, 2022
Length: 14hrs 49mins
Edition : 1st
Language : English
ISBN-13 : 9781803242125
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Product Details

Publication date : Apr 28, 2022
Length: 14hrs 49mins
Edition : 1st
Language : English
ISBN-13 : 9781803242125
Category :
Languages :
Concepts :

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Frequently bought together


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Total $ 122.97 167.97 45.00 saved
Practical Discrete Mathematics
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Advanced Python Programming
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Data Science 101: Methodology, Python, and Essential Math
$9.99 $54.99
Total $ 122.97 167.97 45.00 saved Stars icon
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Table of Contents

19 Chapters
Introduction to Data Science 101 Chevron down icon Chevron up icon
Best Language for Data Science Chevron down icon Chevron up icon
Data Science Methodology Chevron down icon Chevron up icon
Data Science Through Chatbot Chevron down icon Chevron up icon
Libraries, APIs, Datasets Chevron down icon Chevron up icon
GitHub Chevron down icon Chevron up icon
Installation / Jupyter / Comments (Windows and MacOS/Jupyter Notebook) Chevron down icon Chevron up icon
Introduction to Data Science in Python - Python Fundamentals Chevron down icon Chevron up icon
Introduction to Data Science in Python - Decision and Looping Structures Chevron down icon Chevron up icon
Introduction to Data Science in Python - Python Functions Chevron down icon Chevron up icon
Introduction to Data Science - Nested Data, Iteration, and List Comprehension Chevron down icon Chevron up icon
Introduction to Data Science in Python - Learn NumPy Chevron down icon Chevron up icon
Introduction to Data Science in Python - Pandas Chevron down icon Chevron up icon
Introduction to Data Science in Python - Python Activity Solutions Chevron down icon Chevron up icon
Essential Math for Data Science - Linear Algebra Made Easy Chevron down icon Chevron up icon
Essential Math for Data Science - Mathematical Structures Chevron down icon Chevron up icon
Essential Math for Data Science - Introduction to Probability Chevron down icon Chevron up icon
Essential Math for Data Science - Random Variables and Multiple Variables Chevron down icon Chevron up icon
Essential Math for Data Science - Statistical Inference Chevron down icon Chevron up icon

Customer reviews

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N/A Jan 30, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Feefo Verified review Feefo
Felix May 08, 2024
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
Sadly, api pushshift does not work anymore. An Update with other API-Alternatives would be appreciated.
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