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Introduction to Data Science in Python

introduction to data science coursera assignment 1

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan . 

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  • Paid plan:  Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: This course will introduce the learner to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions. The course will also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis. The course will end with a statistics primer, showing how various statistical measures can be applied to pandas DataFrames. By the end of the course, students will be able to take tabular data, clean it,  man…

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Didn't find what you were looking for? See also: Python , Science , R Programming , Software / System Engineering , and English (FCE / CAE / CPE) .

About this course: This course will introduce the learner to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions. The course will also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis. The course will end with a statistics primer, showing how various statistical measures can be applied to pandas DataFrames. By the end of the course, students will be able to take tabular data, clean it,  manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.

Who is this class for: This course is part of “Applied Data Science with Python“ and is intended for learners who have basic python or programming background, and want to apply statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight into data. Only minimal statistics background is expected, and the first course contains a refresh of these basic concepts. There are no geographic restrictions. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers.

Taught by:   Christopher Brooks

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

  • Video: Introduction to Specialization
  • Reading: Syllabus
  • Reading: Help us learn more about you!
  • Video: Data Science
  • Reading: 50 years of Data Science, David Donoho (optional)
  • Video: The Coursera Jupyter Notebook System
  • Notebook: Week 1 Lectures Jupyter Notebook
  • Video: Python Functions
  • Video: Python Types and Sequences
  • Video: Python on Strings
  • Video: Python Demonstration: Reading and Writing CSV files
  • Video: Python Dates and Times
  • Video: Advanced Python Objects, map()
  • Video: Advanced Python Lambda and List Comprehensions
  • Video: Advanced Python Demonstration: The Numerical Python Library (NumPy)
  • Video: Introduction
  • Notebook: Week 2 Lectures Jupyter Notebook
  • Video: The Series Data Structure
  • Video: Querying a Series
  • Video: The DataFrame Data Structure
  • Video: DataFrame Indexing and Loading
  • Video: Querying a DataFrame
  • Video: Indexing Dataframes
  • Video: Missing Values
  • Discussion Prompt: The Ethics of Using Hacked Data
  • Notebook: Assignment 2
  • Notebook: Week 3 Lectures Jupyter Notebook
  • Video: Merging Dataframes
  • Video: Pandas Idioms
  • Video: Group by
  • Video: Scales
  • Video: Pivot Tables
  • Video: Date Functionality
  • Discussion Prompt: Goodhart's Law
  • Notebook: Assignment 3
  • Notebook: Week 4 Lectures Jupyter Notebook
  • Video: Distributions
  • Video: Hypothesis Testing in Python
  • Discussion Prompt: The End of Theory
  • Discussion Prompt: Science Isn't Broken: p-hacking activity
  • Notebook: Assignment 4 - Project
  • Reading: Post-course Survey
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IMAGES

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    My solutions for the Introduction to Data Science Coursera course. Assignment 1 - Twitter Sentiment Analysis in Python Complete Twitter sentiment analysis that involves collecting data from the Twitter API and computing sentiment or "mood" scores from the tweets.

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    WEEK 1 In this week you'll get an introduction to the field of data science, review common Python functionality and features which data scientists use, and be introduced to the Coursera Jupyter Notebook for the lectures. All of the course information on grading, prerequisites, and expectations are on the course syllabus, and you can find more ...

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  20. Statistics for Data Science Essentials

    Week 1: Getting Started with Statistics for Data Science. Module 1 • 4 hours to complete. In the first week of the course, we'll introduce you to a broad definition of data science and go over some of its main building blocks. To prepare, we'll spend some time reviewing discrete math fundamentals.

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  22. Introduction to R Programming for Data Science

    Welcome to Introduction to R Programming for Data Science • 3 minutes • Preview module. Introduction to R Language • 2 minutes. Basic Data Types • 5 minutes. Math, Variables, and Strings • 4 minutes. R Environment • 4 minutes. Introduction to RStudio • 3 minutes. Writing and Running R in Jupyter Notebooks • 4 minutes. 1 reading ...

  23. Coursera: Introduction to Data Science in Python Week 1 Quiz Answers

    Coursera: Introduction to Data Science in Python Week 1 Quiz Answers and Programming Assignment SolutionsCourse:- Introduction to Data Science in PythonOrgan...