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
| Basic Info | Course 1 of 5 in the Applied Data Science with Python Specialization |
| Level | Intermediate |
| Language | English, Subtitles: Vietnamese |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
- Video: Introduction to Specialization
- Материал для самостоятельного изучения: Syllabus
- Материал для самостоятельного изучения: Help us learn more about you!
- Video: Data Science
- Материал для самостоятельного изучения: 50 years of Data Science, David Donoho (optional)
- Video: The Coursera Jupyter Notebook System
- Блокнот: Week 1 Lectures Jupyter Notebook
- Video: Python Functions
- Video: Python Types and Sequences
- Video: Python More 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
- Блокнот: 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
- Вопрос для обсуждения: The Ethics of Using Hacked Data
- Блокнот: Assignment 2
- Блокнот: Week 3 Lectures Jupyter Notebook
- Video: Merging Dataframes
- Video: Pandas Idioms
- Video: Group by
- Video: Scales
- Video: Pivot Tables
- Video: Date Functionality
- Вопрос для обсуждения: Goodhart's Law
- Блокнот: Assignment 3
- Блокнот: Week 4 Lectures Jupyter Notebook
- Video: Introduction
- Video: Distributions
- Video: More Distributions
- Video: Hypothesis Testing in Python
- Вопрос для обсуждения: The End of Theory
- Вопрос для обсуждения: Science Isn't Broken: p-hacking activity
- Блокнот: Assignment 4 - Project
- Материал для самостоятельного изучения: Post-course Survey
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Really good!!!
I've Loved a lot and everything is at one stop to learn Data sciences in Python
it is a really good class, very informative and gives you a really good base in how to use pandas, numpy. my only complaint was that is was to fast. I did not feel that there was enough explanation for each concept. the homework took me a lot longer then the time it said it would.
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They way of teaching is perfect. I think the students can grasp the concept more easily and permanently through this approach. Good effort!
Wonderful course.