Computing in Python III
Data Structures
Introduction to Python Programming,
Build on your existing knowledge of conditionals, loops, and functions by studying more about complex Python data structures, including strings, lists, dictionaries, and file input and output. Organized into five chapters, this course starts by covering the basics of data structures, then moves on to these four common data structures in Python:
Strings let you perform far more complex reasoning with text.
Lists let you process long lists of data, and even lists of lists of data for more complex reasoning.
Dictionaries let you more clearly code for complex types of data, and even simulate some basic elements of object-oriented programming.
File input and output brings your programs to life, allowing you to persist data across executions of the same program.
By the end of this course, you'll be able to write even more complex programs in Python that process and persist complex data structures. For example, you'll be able to write an ongoing gradebook application that tracks and updates your average over time, a program to calculate the net force based on several force magnitudes and directions, or a program that can turn a string like this into a StRiNg LiKe tHiS.
Structurally, the course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, you'll complete both multiple choice questions and coding problems to demonstrate your knowledge of the material that was just covered.
What you'll learn
- Strings, including advanced string methods.
- Tuples and lists, including multi-dimensional lists.
- File input and output, including multiple modes for file access.
- Dictionaries, including replicating object-oriented reasoning using dictionaries.
- Using control structures with data structures, such as looping over lists or error handling with files.
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Rating | 5.0★ based on 8 ratings |
---|---|
Length | 5 weeks |
Effort | 5 weeks, 9–10 hours per week |
Starts | On Demand (Start anytime) |
Cost | $149 |
From | GTx, The Georgia Institute of Technology via edX |
Instructor | David Joyner |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming |
Tags | Computer Science |
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What people are saying
well demonstrated with examples
This theoretical explanation was well demonstrated with examples.
why tuples are better
Why tuples are better than lists in some context.
found some problem sets
I found some problem sets to be particularly challenging; however, persistence and reaching out to the awesome TA's usually provided a breakthrough.
programmed - without taking
I have programmed - without taking any course - in Python 2.x more than 10 years ago (and I forgot most of it).
emphasis on problems rather
I like the fact that they put more emphasis on problems rather than just teaching theory.
10 years ago
absolutely amazing lecturer
Absolutely amazing lecturer.
first step up
I am interested in data science and was looking for a Python course as a first step up.
required 20 words
I could do this in much less than the required 20 words, just say super.
challenging but doable
Great course overall, very comprehensive, challenging but doable.
about dictionaries
This course teach me about dictionaries and tuples.
additional resources
I thoroughly enjoyed the course .Especially how it was structured and the links to additional resources.
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Rating | 5.0★ based on 8 ratings |
---|---|
Length | 5 weeks |
Effort | 5 weeks, 9–10 hours per week |
Starts | On Demand (Start anytime) |
Cost | $149 |
From | GTx, The Georgia Institute of Technology via edX |
Instructor | David Joyner |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming |
Tags | Computer Science |
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