Episodes
Detailed
Compact
Art
Reverse
October 1, 2016
Explore the nature of programming and how programming a computer is different than using a computer.
October 1, 2016
In this lecture we learn abut how the computer processes and stores programs. We learn about the CPU, Memory, Storage and Input / Output devices are brought together to write a program.
October 1, 2016
We look at how writing programs is just another form of communication. Instead of communicating with another person, we are communicating our ideas to a computer.
October 1, 2016
We look at the basics of the Python language and how we write code in Python to communicate sequential steps, conditional steps and repeated steps.
September 30, 2016
We look at Python's reserved words, how we name and use variables, why we choose meaningful (mnemonic) variable names and how assignment statements function.
September 30, 2016
We look at how we use various numerical and string operations to compute new information and store the new values in variables.
September 30, 2016
The most basic conditional structure is the if statement where we either execute or skip a segment of code based on the results of a logical expression (i.e. asking a question).
September 30, 2016
In this lecture we look at multi-branch if statements and the try-except concept where we can indicate a group of statements to be executed if something goes wrong with a block of statements.
September 30, 2016
We look at how code flows into and out of functions as well has how we pass information into functions and get results returned to us.
September 30, 2016
We look at how to build our own functions using parameters and arguments as well as how we return results to the code that is calling our functions.
September 30, 2016
We look at how we construct a loop so that it runs as long as we want it to run. We learn about iteration variables and exiting loops with the 'break' and 'continue' statements.
September 30, 2016
We learn how to use the 'for' statement in Python to loop through a set of data.
September 30, 2016
Loops have a beginning, middle, and end. We look ant how we construct a loop to look at a list of items one at a time so we can compute an overall maximum, minimum or average.
September 30, 2016
We continue to look at how to construct loops including how to do something special the first time through the loop. We introduce the idea of 'None' which is a way to indicate that a variable is currently empty.
September 30, 2016
We learn how to create string variables and extract portions of the data as well as write simple loops to read through the characters in a string.
September 30, 2016
We learn how to extract substrings using slicing, and use the string library to perform common data extraction operations with strings.
September 30, 2016
We look at how text and lines are represented in files, how we open a file and write a loop to read through all the lines in the file.
September 30, 2016
We look at patterns for reading and processing the data in files. We learn how to check for nonexistent files, and how we process each line within the file.
September 30, 2016
We learn how to put data into lists, take data out of the list and write simple loops to examine the elements of a list.
September 30, 2016
We learn about list slicing, list searching, and using pre-defined functions with lists.
September 30, 2016
We learn how to parse strings pull sub-strings out of a string using the split() function.
September 30, 2016
We compare and contrast how Python lists and dictionaries are structured internally. How we use position to index lists and use keys to index dictionaries.
September 30, 2016
We look at how we can use dictionaries to count the frequencies of many things at the same time. We learn how the key and value are related in a dictionary and example the get method to retrieve values from a Python dictionary.
September 30, 2016
In this segment we bring everything together, reading a file, parsing the lines, and computing the frequencies of the words in the file. This is an important moment that pulls from everything we have learned so far.
September 30, 2016
We look at the basic syntax and capabilities of Python tuples. We explore the concept of immutability, and we compare tuples to lists and strings.
September 30, 2016
We look at how we sort lists, dictionaries, and lists of tuples in Python.
September 30, 2016
Worked Example: Sorting Dictionaries
September 30, 2016
We look at the syntax of regular expressions and how to use them to search through text data.
September 29, 2016
In this segment we learn to pull out data from strings after a regular expression has found a match.
September 29, 2016
We look at how some of the string parsing we have done in earlier chapters can be easily done with regular expressions.
September 29, 2016
We take a very brief look at how software communicates across the Internet using TCP/IP.
September 29, 2016
In this section we look at the HTTP protocol that is used to move documents between web servers and web browsers.
September 29, 2016
We write a simple Python program that connects to a web server and retrieves a web document. It is a very simple web browser.
September 29, 2016
We explore how characters are encoded when they are transported across the network.
September 29, 2016
We write an even simpler Python program to retrieve a web page using the urllib library in Python.
September 29, 2016
Now we will look at the HypertextMarkup Language (HTML) that we retrieved using Python and extract links form that HTML. We are slowly building a very simple web search engine.
September 29, 2016
We look at two different ways to format data for transmission across the network including JavaScript Object Notation (JSON) and eXtended Markup Language (XML).
September 29, 2016
We look at how data is represented using the XML format.
September 29, 2016
We look at how we can use XML Schema to determine whether or not a particular bit of XML is valid.
September 29, 2016
We learn about the popular JSON data format and how to handle the JSON data in Python.
September 29, 2016
We talk briefly about how applications can be built over time to depend on services provide other applications.
September 29, 2016
We explore using a Google API that can be used to query location data and parse the JSON that is returned.
September 29, 2016
We explore the use of OAuth to communicate sign requests to establish identity when using the Twitter API.
September 29, 2016
We look at how Python mentions objects in its documentation as well as talk about why philosophy of object-oriented programming. We explore some OOP terms like class, object, instance, method, and attribute.
September 29, 2016
We look at how use create a new class in Python and then construct a new object from that class. We also look at some of the Python objects (like strings) that we have been using all along.
September 29, 2016
We look at how we as the developers of a Python class can interact with the moment of construction and destruction of various objects created using the class.
September 29, 2016
We look at how we can make a new class by inheriting all of the attributes and methods of a parent class and then extend the new class with additional attributes and methods.
September 29, 2016
We look at the history of database systems, learn the terminology of database systems, and review some of the common database systems that are in use.
September 29, 2016
We learn about how we can use Structured Query Language (SQL) to insert (create), read, update, and delete data in a single database table.
September 29, 2016
We look at how we can take the various data elements that will be modeled in an application and distribute them across several tables efficiently. We learn about the basic rules of database design.
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