Pythonista - I (Online Courses)
Elevate your career trajectory with our premier online course, designed to sharpen your competitive edge. Explore our curated selection of top-tier digital programs to hone your skills and propel your professional journey forward. Experience transformative learning tailored to empower your career advancement in today's dynamic landscape.
Price on Request
Start Learning
This Course Includes
-
59 hours 35 minutesof self-paced video lessons -
37 Programscrafting your path to success -
Completion Certificateawarded on course completion
Automation Testing for Python
Price on Request
50 minutes
This course explores the prominent frameworks for testing Python-based applications, how to implement tests using Pytest and PyCharm, and also Pytest test parameterization. Begin this 14-video course with a look at the concept of automated testing and classifying the different types of automation testing. Then view the prominent Python testing frameworks, and features of DocTest, Nose, and UnitTest that can be used to automate testing of Python-based applications. Discover how to implement unit testing in Pytest by using the PyCharm integrated development environment (IDE), and the procedure to parameterize tests by using Pytest. Learn about configuring Robot and executing Python tests using the Robot framework; build and test application programming interfaces (API) using Flask, and explore the process of testing APIs built in Flask using Postman. Also learn how to configure the Behave framework for Python testing by writing feature files. To conclude the course, learners observe how to automate testing of web components by using Selenium with Python.
Perks of Course
Certificate: Yes
CPD Points: 48
Compliance Standards: AICC
AWS Lambdas in Python: Serverless Compute in Python with AWS Lambda
Price on Request
1 hour 55 minutes
AWS Lambda is a serverless, event-driven compute service, meaning that it allows you to execute code when a specific event occurs, and abstracts the burden of maintaining infrastructure from you, the developer. Lambda functions are extremely powerful, but generally best-suited for lightweight interactive applications. Explore serverless computing and the benefits of AWS Lambdas. Discover the AWS Lambda dashboard and deploy a lambda function using Python runtime. Practice using blueprints and investigate the role of AWS Identity and Access Management in the successful outcome of a lambda function. Finally, configure a new REST API trigger through the API gateway service and expose that REST API using the curl utility. When this course is completed, you will recognize the roles and policies required for a lambda to run, and be able to create, deploy, and test lambda functions.
Perks of Course
Certificate: Yes
CPD Points: 114
Compliance Standards: AICC
AWS Lambdas in Python: Using AWS Lambda with Containers, SES, SNS, & DynamoDB
Price on Request
2 hour 5 minutes
A major benefit of using AWS Lambda is that you can easily integrate with other powerful AWS services like the Elastic Container Registry (ECR), AWS Simple Email Service (SES), DynamoDB, or Simple Notification Service (SNS). Learn how to deploy a lambda function based off a Docker container image and upload it to AWS via the ECR. Explore adding functionality to your lambda so that it can connect to Twitter. Modify your lambda to write out tweets to an S3 bucket and send automated emails. Finally, create a lambda function that triggers on a notification from an SNS and write out the contents of that notification to a DynamoDB table. Upon completion of this course, you will be able to easily deploy lambda functions as container images and seamlessly integrate AWS Lambda with ECR, SES, DynamoDB, and SNS.
Perks of Course
Certificate: Yes
CPD Points: 123
Compliance Standards: AICC
Complex Data Types in Python: Shallow & Deep Copies in Python
Price on Request
45 minutes
Explore copying operations on containers in Python in this 9-vdeo course, which examines the subtle distinction between shallow and deep copies. Changes made to shallow copies affect the original whereas with deep copies they do not. Learners begin by observing Jupyter notebook in Python, where you will be performing shallow and deep copies of Python strings. You will learn how to create shallow copies of lists, and then create deep copies of lists where changes to the copy do not affect the original. Following this, you will begin working with tuples, a process which you will discover is quite simple because tuples are immutable. So you will learn how to create shallow and deep copies of tuples. You will also learn how deep copies of dictionaries work, and perform shallow and deep copies of sets. In the closing exercise, learners are asked to recall how shallow and deep copies work for complex data types.
Perks of Course
Certificate: Yes
CPD Points: 44
Compliance Standards: AICC
Complex Data Types in Python: Working with Dictionaries & Sets in Python
Price on Request
55 minutes
This 9-video course helps learners explore dictionary data type in Python. Dictionaries are associative containers used to store key-value pairs. Given a key, finding the associated value is optimized by Python to be extremely efficient. First, receive an introduction to dictionaries in Jupyter Notebook in Python. You will learn how to create and initialize dictionaries, then learn about nesting complex data types within dictionaries. Continuing with the study of Python dictionaries, you will explore what functions and methods can be invoked on these dictionaries, such as modifying and updating dictionaries using dictionary methods. Next, you will be introduced to sets, another commonly used complex data type that Python supports. You will then create and initialize sets. This leads on to performing set operations such as union, intersection difference, and other set operations. You will also examine nested lists, and work with nested types within other complex data types. In the final tutorial, you will learn how to convert lists to dictionaries and vice versa. The concluding exercise entails recalling features of dictionaries and sets.
Perks of Course
Certificate: Yes
CPD Points: 53
Compliance Standards: AICC
Complex Data Types in Python: Working with Lists & Tuples in Python
Price on Request
1 hour 40 minutes
Learn how to work with lists, tuples, and strings in Jupyter notebook in Python in this 14-video course. You will discover similarities and differences between tuples and lists and see how strings are essentially just a list of characters. Begin with an introduction to lists, and then create and initialize lists in Python. You will then access and update list elements; add, remove, sort, and reverse elements from a list; execute built-in functions with lists, and create new lists from existing lists by using slicing operations. Next, examine how to extract specific elements from the original list using step size; perform list functions on strings; invoke functions on the string object; and access substrings with slicing operations. Receive an introduction to tuples, exploring the similarities between lists and tuples, then move on to understanding tuple immutability by specifying differences between lists and tuples. Then an introduction to other complex data types and using dictionaries and sets in Python. The concluding exercise concerns recalling differences and similarities between lists and tuples.
Perks of Course
Certificate: Yes
CPD Points: 99
Compliance Standards: AICC
Conditional Statements & Loops: Advanced Operations Using for Loops in Python
Price on Request
1 hour 5 minutes
Explore how iterating over elements using for loops can be controlled using the break and continue statements in Python. Creating sequences from other sequences using comprehensions is also covered in this 9-video course. Key concepts covered here include how to terminate a for loop when a specific condition is met using the break statement; learning how the break statement affects the code in the else block of a for loop; and observing how to skip an iteration of a for loop when a specific condition is met using the continue statement. Next, learn how to use the continue statement along with the break statement within the same for loop; learn the fact that no action is performed under specific conditions by using the pass statement; and create a list out of the contents of another list using a comprehension. Finally, you will learn about conditions in list comprehensions in order to filter elements used in the source list and to define values in the newly created list.
Perks of Course
Certificate: Yes
CPD Points: 65
Compliance Standards: AICC
Conditional Statements & Loops: If-else Control Structures in Python
Price on Request
1 hour 40 minutes
Learners will explore implementations of the order of precedence of operators, using if-elif-else statements to evaluate multiple conditions and conversions between various data types in Python, in this 15-video course. Key concepts covered here include how conditions in Python work, and how to evaluate conditions by involving primitive data types using if statements and complex data types using if statements. Next, evaluate multiple conditions for decision making with nested control structures; identify how to use the if-else statement to make decisions involving complex data types such as lists, tuples, and dictionaries; and learn how to convert an integer to a float and a float or an integer to a string, and vice-versa. Learners then observe how to convert primitive data types to complex data types, to convert between various complex data types, and to convert between various complex data types and view base conversions with Python built-in functions; and to solve various programming problems with Python built-in methods. Finally, you will learn to solve various programming problems by using if-elif-else statements and nested if-else statements.
Perks of Course
Certificate: Yes
CPD Points: 100
Compliance Standards: AICC
Conditional Statements & Loops: The Basics of for Loops in Python
Price on Request
1 hour
Loops are one way to perform the same operations repeatedly in a program. For loops are the control structure to use when the repeated operations are performed on a sequence such as a list or a tuple. In this 9-video course, you will explore different ways to iterate over a sequence using for loops. Key concepts covered in this course include how to use for loops to process elements in a list and characters in a string; and how to code for loops to iterate over values in a tuple and the keys and values in a dictionary. Next, learn the function of associating an else block with a Python for loop; include if-else statements and other for loops within a for loop; how to generate a sequence of consecutive integers with the range function; and how to use the range function to iterate over a large range of values and apply it within nested for loops. Finally, observe how to write for loops in order to iterate over 1-dimensional and 2-dimensional sequences.
Perks of Course
Certificate: Yes
CPD Points: 61
Compliance Standards: AICC
Conditional Statements & Loops: While Loops in Python
Price on Request
1 hour 20 minutes
While loops are one way to keep repeating a set of actions until a specific condition is met in Python. In this 11-video course, learners explore the use of while loops, considerations when implementing while loops, and use cases for while loops and for loops. Key concepts covered here include implementing a basic while loop and recognizing what conditions cause it to become an infinite loop; learning to use while loops to carry out actions while evaluating expressions based on numerical and string data; and examining while loops whose iterations depend on user input data. Next, learn syntax for defining while loops within a single line; learn to iterate over a list of elements with while loops; and learn to iterate over multiple lists and tuples with while loops. Learn when it is appropriate to use break keyword to stop a while loop, and learn to break out of a while loop and recognize use of the pass keyword within such loops. Finally, learn skip steps in individual iterations of a while loop using the continue statement.
Perks of Course
Certificate: Yes
CPD Points: 79
Compliance Standards: AICC
Core Statistical Concepts: Statistics & Sampling with Python
Price on Request
1 hour 35 minutes
Data is one of the most valuable assets a business has, but it's only as valuable as the methods used to interpret it. Data science, which at its core includes statistics and sampling, is the key to data interpretation. In this course, practice using the pandas library in Python to work with statistics and sampling. Practice loading data from a CSV file into a pandas DataFrame. Compute a variety of statistics on data. While doing so, see how to visualize the relationship between data and computed statistics. Moving along, implement several sampling techniques, such as stratified sampling and cluster sampling. Then, explore how a balanced sample can be created from an imbalanced dataset using the imblearn module in Python. Upon completion, you'll be able to generate samples and compute statistics using various tools and methods.
Perks of Course
Certificate: Yes
CPD Points: 95
Compliance Standards: AICC
Dash Python Framework: Creating Widgets in Dash Apps
Price on Request
2 hour
The Dash DAQ library can be used to represent data in ways that correspond to real-world physical measurement mechanisms, such as switches, thermometers, knobs, dials, gauges, LED displays, and tanks. In this course, you'll learn how to work with this library. In addition, you'll practice creating widgets using Dash core components. You'll also create Dropdowns, TextAreas, RadioButtons, and Checklists. Finally, you'll cover two important aspects of building web apps - building tabbed apps with different controls on each tab and accepting user upload of files. You'll build a web app that accepts a file for upload, either via drag-and-drop or via direct user navigation, and then checks whether the file is a .csv file and if so, displays the contents of that file in a DataTable.
Perks of Course
Certificate: Yes
CPD Points: 118
Compliance Standards: AICC
Dash Python Framework: Dash for Interactive Web Apps
Price on Request
1 hour 30 minutes
With Dash, you can create interactive web apps with elements such as buttons, dropdowns, sliders, range sliders, checkboxes, date pickers, and more. In this course, you'll learn how to get started with Dash, beginning with installing Dash and various extension libraries using the pip package installer. You'll move on to building web apps using Dash and the Plotly Express library. You'll also work with two other important Dash extension libraries - the Dash Core Components library and the Dash HTML Components library. You'll put all of these libraries together while exploring some of the default interactivity features, such as zooming and panning charts. You'll create a callback app where the title of a chart updates based on the values on a range slider before creating a more refined app with a callback that updates the chart itself and not just the title. Finally, you'll build a fully-fledged interactive scatter plot.
Perks of Course
Certificate: Yes
CPD Points: 92
Compliance Standards: AICC
Dash Python Framework: Leveraging Dash with User Input & Dash DataTable
Price on Request
1 hour 40 minutes
If you've used Dash before, you'll know how quickly the native HTML table abstraction from dash_html_components can become complicated and cumbersome due to the need to create a TR tag for each row and then individual TD tags within each TR tag for each cell value. Using the dash DataTable abstraction mitigates all of these weaknesses. In this course, you'll practice this technique before using the Dash data table to display data in the form of tables in Dash apps. You may also know that you can harness the power of Dash using HTML components or components from the Dash Core Component library. In this course, you'll also get a chance to work with user input and buttons in Dash apps using the most appropriate components.
Perks of Course
Certificate: Yes
CPD Points: 101
Compliance Standards: AICC
Data Science Statistics: Using Python to Compute & Visualize Statistics
Price on Request
1 hour 15 minutes
Learners continue their exploration of data science in this 10-video course, which deals with using NumPy, Pandas, and SciPy libraries to perform various statistical summary operations on real data sets. This beginner-level course assumes some prior experience with Python programming and an understanding of basic statistical concepts such as mean, standard deviation, and correlation. The course opens by exploring different ways to visualize data by using the Matplotlib library, including univariate and bivariate distributions. Next, you will move to computing descriptor statistics for distributions, such as variance and standard error, by using the NumPy, Pandas, and SciPy libraries. Learn about the concept of the z-score, in which every value in a distribution is expressed in terms of the number of standard deviations from the mean value. Then cover the computation of the z-score for a series using SciPy. In the closing exercise, you will make use of the matplotlib data visualization library through three points represented by given coordinates, then enumerate all of the details which are conveyed in a Boxplot.
Perks of Course
Certificate: Yes
CPD Points: 75
Compliance Standards: AICC
Data Structures & Algorithms in Python: Fundamental Data Structures
Price on Request
1 hour 20 minutes
Explore Python data structures and delve into the details of some of the basic structures, such as linked lists, stacks, and queues. Key concepts covered in this 12-video course include the metrics on which algorithms and operations on data are evaluated; learning how the performance of operations and algorithms is expressed in terms of size of input; and learning about linked lists and their contents and structure. Next, study different ways in which nodes can be added to a linked list and how search operations work on this data structure; learn methods to remove nodes from a linked list and the process of reversing the order of nodes in this data structure; and learn techniques used to keep track of numbers of elements in linked lists. You will examine workings of a stack data structure, including the addition and removal of elements; learn some of the operations on stacks, such as ISEMPTY and ISFULL, and the complexities of different stack operations; and learn the queue data structure and how to compare it to stacks.
Perks of Course
Certificate: Yes
CPD Points: 79
Compliance Standards: AICC
Data Structures & Algorithms in Python: Implementing Data Structures
Price on Request
1 hour 30 minutes
Examine operations that have different values of time complexity and delve into implementation of basic data structures, such as linked lists, stacks, and queues in Python, in this 13-video course. Key concepts covered here include operations that run in constant time regardless of input; code whose time complexity varies directly with value of input; and tasks whose time complexity varies linearly with size of input. Next, you will learn about operations whose time complexity varies as the square of input size; how to use native queue class of Python and perform standard queue operations; and how to code a queue class for many standard queue operations, such as enqueue and dequeue. Then, learn how a Python list can be used as a stack by loading and unloading elements, and how to implement a custom stack class for common stack operations. Finally, study code functions to perform search and delete operations in linked lists and reverse the ordering of its nodes; and create a linked list and test out various operations that have been defined.
Perks of Course
Certificate: Yes
CPD Points: 89
Compliance Standards: AICC
Data Structures & Algorithms in Python: Implementing Sorting Algorithms
Price on Request
1 hour 30 minutes
Examine the Python implementation of common sorting algorithms such as selection sort, bubble sort, and insertion sort, as well as divide and conquer sorts such as shell sort, merge sort, and quicksort, in this 10-video course. Key concepts covered in this course include how to write the code to implement a selection sort; how to implement the bubble sort algorithm in Python; and how to code a function to implement the insertion sort algorithm. Next, you will observe how to write the code to implement the divide-and-conquer shell sort algorithm; how to invoke the shell sort algorithm on an array of integers and examine the output at each iteration to understand how it works; and how to code a function to implement the merge sort algorithm and test it on an array of integers. Finally, learn how to write the partition and quicksort functions in order to implement a quicksort; and how to apply quicksort on an array of integers and analyze the results at each iteration to understand how the algorithm works.
Perks of Course
Certificate: Yes
CPD Points: 70
Compliance Standards: AICC
Data Structures & Algorithms in Python: Implementing Trees & Graphs
Price on Request
1 hour 25 minutes
Explore implementing trees and graphs in Python in this 14-video, hands-on course that contains only labs. In this course, learners will use Python 3 and Jupyter Notebooks as their IDE (integrated development environment). In the course labs, you will implement a binary search, define a binary search tree, and use code functions to work with those data structures. Next, you will implement algorithms to traverse trees, including how to perform a breadth-first traversal and depth-first traversal of the tree. Continue by examining graph data structure, and implementing different representations of graphs in Python by using an abstract class for a graph to represent graphs as both an adjacency set and an adjacency matrix. You will implement algorithms to traverse such graphs, including a breadth-first traversal and a depth-first traversal. This course then demonstrates how to run a test to check its implementation. Finally, learners observe how to implement a topological sort for a specific type of graph which is both directed as well as acyclic.
Perks of Course
Certificate: Yes
CPD Points: 85
Compliance Standards: AICC
Data Structures & Algorithms in Python: Sorting Algorithms
Price on Request
1 hour 30 minutes
In this 11-video course, learners explore workings of some of the most widely used sorting algorithms in Python and examine how their performance affects various measures. Key concepts covered here include various properties of sorting algorithms when selecting the right one for your data; the operations involved when sorting a list of values by using the selection sort algorithm; and the process of a bubble sort when applied to a list of values. Next, you will learn about the performance of the bubble sort on various measures such as time, space, and number of swaps; how to describe the steps involved in performing an insertion sort and compare it to the bubble sort; and learn the workings of the shell sort and the performance metrics of this divide and conquer algorithm. Finally, you will learn the process of sorting a list of elements using merge sort and list the complexity of this algorithm on various measures; and learn how the quicksort algorithm partitions and sorts a list of elements.
Perks of Course
Certificate: Yes
CPD Points: 74
Compliance Standards: AICC
Data Structures & Algorithms in Python: Trees & Graphs
Price on Request
1 hour 25 minutes
This 13-video course explores the theory of graph and tree data structures in Python. Learners will examine a specific type of tree: the binary search tree, its structures and properties. You will then observe how to execute common tasks in binary tree; examine the binary search algorithm; and review data structures of linked lists, stacks, and queues. Next, learners will examine how a binary tree structure offers several applications that cannot be done by using stacks or queues. The course demonstrates different depth first traversals, including pre-order, in-order traversals, and post-order traversals. Explore graphs, which are data structures used to model relationships, and different representations of a graph, and learn to model a vertex. Learners continue by observing how to represent an adjacency list as a graph, and examining the adjacency matrix, the adjacency list, and the adjacency set. Then you will explore graph traversal algorithms, including the topological sort. Finally, learn how to traverse through each of the vertices in a graph.
Perks of Course
Certificate: Yes
CPD Points: 92
Compliance Standards: AICC
Data Wrangling in Python Bootcamp: Session 1 Replay
Price on Request
2 hour 40 minutes
This is a recorded Replay of the Data Wrangling in Python Live session that ran on July 26th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 160
Compliance Standards: AICC
Data Wrangling in Python Bootcamp: Session 1 Replay
Price on Request
3 hour
This is a recorded Replay of the Data Wrangling in Python Live session that ran on February 23rd.
Perks of Course
Certificate: Yes
CPD Points: 179
Compliance Standards: AICC
Data Wrangling in Python Bootcamp: Session 2 Replay
Price on Request
2 hour 40 minutes
This is a recorded Replay of the Data Wrangling in Python Live session that ran on February 24th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 160
Compliance Standards: AICC
Data Wrangling in Python Bootcamp: Session 2 Replay
Price on Request
2 hour 30 minutes
This is a recorded Replay of the Data Wrangling in Python Live session that ran on July 27th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 151
Compliance Standards: AICC
Data Wrangling in Python Bootcamp: Session 3 Replay
Price on Request
2 hour 20 minutes
This is a recorded Replay of the Data Wrangling in Python Live session that ran on July 28th at 11 AM ET
Perks of Course
Certificate: Yes
CPD Points: 138
Compliance Standards: AICC
Data Wrangling in Python Bootcamp: Session 3 Replay
Price on Request
2 hour 40 minutes
This is a recorded Replay of the Data Wrangling in Python Live session that ran on February 25th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 159
Compliance Standards: AICC
Excel with Python: Constructing Data Visualizations
Price on Request
1 hour
This course explores how to use Python's openpyxl library to build visualizations such as line, bar, and bubble charts in Excel. In its 11 videos, you will examine how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation, before learning how to create line and bar charts in Excel, and learning how to use Python to control several properties of those charts, including line weights and style, data for the reference axes, formatting, and the position of ticks on those axes. Learners will observe how to construct data visualizations in Excel using Python. This course then demonstrates common types of visualizations that are supported in Excel, and how to programmatically replicate those visualizations from within Python. Finally, learners will observe demonstrations of the use of bubble charts to display three dimensions on a two-dimensional chart as well as stock charts to represent the opening, high, low, and closing prices of stocks in a single data visualization for the financial markets.
Perks of Course
Certificate: Yes
CPD Points: 60
Compliance Standards: AICC
Excel with Python: Performing Advanced Operations
Price on Request
1 hour 30 minutes
Learners can explore complex operations in Microsoft Excel workbooks, including the use of conditional formatting, named ranges, and merged cells, in this 17-video course. Microsoft Excel is the best prototyping tool for data analysis, an interactive functional programming environment, and a forerunner of Python. Begin by exploring how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation. Then observe the formatting, alignment, and other aesthetics in Python. You will work with the Python library openpyxl; examine data analysis, the use of pivot tables, and the locking of cell references by using the $ operator; and learn how to perform complex data analysis operations using pivot tables, sorting and filtering, and formulae with both absolute and relative cell references to enable efficient copy paste. You will learn to control the workbook appearance using conditional formatting and styles. Finally, this course demonstrates how to leverage the Python Pandas library to read a spreadsheet, to group and analyze data.
Perks of Course
Certificate: Yes
CPD Points: 89
Compliance Standards: AICC
Excel with Python: Working with Excel Spreadsheets from Python
Price on Request
1 hour 15 minutes
This 13-video course explores how Microsoft Excel spreadsheets can be created, opened, and modified programmatically from within Python. Learners will review the Microsoft Excel object model, the attributes of the worksheet cell object which can be leveraged to create and modify workbooks programmatically. First, you will review VBA (Visual Basic for Applications) technology, before exploring how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation. Then you will learn how to use openpyxl (open pixel library) to manipulate Excel's object model programmatically from within Python. Continue by learning how to write spreadsheets by using openpyxl, and examining how existing Excel workbooks can be opened, as well as how new spreadsheet files can be created, and written out to disk. Finally, you will learn how Python iterators and indexing can be used to access and manipulate individual cells, ranges consisting of many cells, as well as entire rows and columns.
Perks of Course
Certificate: Yes
CPD Points: 76
Compliance Standards: AICC
Flask in Python: An Introduction to Web Frameworks & Flask
Price on Request
50 minutes
Explore the steps involved in a web request and the role of web applications in this web development process in this 8-video course examining various pieces that can make up a web application, and the role of the web framework in defining it. Begin by observing a widely used framework, often defined as a microframework, written in the Python language, which is Flask. You will then explore the features of the Flask framework that are available either out of the box or via extensions. Following on from this, you will delve into the roles of routes in a Flask application and the options available when defining a route function. You will learn how to recognize the need for templates when defining a web site and describe the use of jinja for this purpose. The final tutorial in this course focuses on some of the commonly used extensions in the Flask applications and recalls the purposes they serve.
Perks of Course
Certificate: Yes
CPD Points: 49
Compliance Standards: AICC
Flask in Python: Building a Simple Web Site Using Flask
Price on Request
1 hour 30 minutes
You will begin this 12-video course by learning how to install Flask-a widely used web framework written in Python language-in a virtual environment on your development machine, and then write the code for a simple "Hello World" website by using Flask. You will explore how route definitions can be altered and the benefits of running your Flask app in debug mode. Next, define a route that renders an HTML page when a URL is accessed; download and use some boilerplate HTML files so your website definition need not begin from scratch, and modify the boilerplate cascading style sheet (CSS) and HTML definitions to customize the look of a website. Learn how to generate URLs dynamically by using the url_for function; create a base Jinja template that can be inherited by other templates, along with placeholders that can be overridden; and explore how to inherit the elements from a base Jinja template in a child template HTML file. Finally, learn how to define multiple routes to point to the same route function.
Perks of Course
Certificate: Yes
CPD Points: 89
Compliance Standards: AICC
Flask in Python: User Authentication in a Flask Application
Price on Request
1 hour 35 minutes
In this 14-video course, titled "User Authentication in Flask Applications," you will begin with an introduction to SQL Alchemy, then install it and use it to connect the Flask application-a widely used web framework written in Python language-to a SQLite database. You will observe how to use SQL Alchemy to generate relational database tables for each model defined in an application; execute queries against tables by using a SQL Alchemy model; and how to structure a Flask application for maintenance. Then you will modify import statements to account for restructuring of Flask app and test that functionality has not been affected. Use Bcrypt package to generate hashes of passwords so that they can be stored securely, and create a bespoke validator for fields in your WTForms. Next, learn how to enable users to log in and log out of a Flask application. You will access and display the three most recent reviews posted on your Flask website; learn how to test feedback display functionality; and display images in your Flask website.
Perks of Course
Certificate: Yes
CPD Points: 93
Compliance Standards: AICC
Flask in Python: User Interactions in Flask Applications
Price on Request
1 hour 20 minutes
In this 12-video course, learners discover how to handle errors in Flask-a widely used web framework written in Python language-by serving a custom error page whenever a 404 error is invoked on a website. Learn how to configure a route in your Flask app so that POST requests can be submitted. Next, use the Flask debugger to record information in your application's log; convey the invocation of an operation to end users by using message flashing, and then highlight flashed messages by defining a style for them in a cascading style sheet (CSS) file. Next, explore how to install and use WTForms in Flask application to accept user input for registration, and define a login page by using field definitions and built-in form validations available in WTForms. Then include the two pages defined by using WTForms in the Flask application, and invoke the validators defined for WTForm elements to ensure that the user input is in the correct form. Finally, ensure that all built-in validators applied on the WTForm elements work as expected.
Perks of Course
Certificate: Yes
CPD Points: 80
Compliance Standards: AICC
FSD Development with Python: API Development in Flask
Price on Request
1 hour 20 minutes
Learners discover how to implement a working API (application programming interface) using Python and the Flask framework in this 13-video course. Explore RESTful APIs, practical applications for APIs, and API framework choices for full stack development. Learn more about API scaffolding, HTTP data processing, working with JSON payloads, handling unexpected errors, and testing APIs with Pytest. Begin by learning about benefits of using Python APIs for FSD (full stack development) and examine principles and methods behind RESTful APIs as well as practical applications and considerations for using APIs in FSD. Then compare popular API frameworks for Python and the advantages and disadvantages of each, and explore the benefits of TDD (test-driven development) for API development in Python. Next, learn how to configure and launch a simple endpoint in a Python Flask server application; implement GET and POST operations in a Python Flask API; and handle unexpected errors, implement logging, and learn how to use Pytest to run automated tests against API endpoints. The concluding exercise involves implementing a Python Flask API app with CRUD operations and validating endpoints.
Perks of Course
Certificate: Yes
CPD Points: 78
Compliance Standards: AICC
Functions in Python: Gaining a Deeper Understanding of Python Functions
Price on Request
1 hour 25 minutes
This 13-video course offers learners an in-depth exploration of Python functions, by focusing on nuances such as argument passing by value and reference, and local and global variables. In this course, you will examine how functions are first-class citizens in Python, as with other data types. You will examine how Python allows functions to be stored in variables, passed into other functions as arguments, and returned from functions as return values. Next, you will learn how to identify and apply differences between parsing arguments by value and reference. Examine how Python treats functions on par with other data types, a key attribute of a program seeking to support the functional programming paradigm; and learn how to work with use and throw functions by using lam das. This course then covers how lightweight functions for one-off use called lambda functions or anonymous functions play an important role in keeping Python code both succinct and readable. Finally, you will learn how to appropriately choose between local and global variables for use in your program.
Perks of Course
Certificate: Yes
CPD Points: 85
Compliance Standards: AICC
Functions in Python: Introduction
Price on Request
2 hour 5 minutes
Explore how Python facilitates code reuse by using functions in this 17-video course, which shows learners how to define functions, learn passing arguments to functions, and returning values from functions. The functions you will examine change the state of the program, may have side effects, and have observable effects other than their return values. Since functions with side effects are hard to parallelize and use in a distributed environment, you will learn correct ways of returning values from functions. First, you will learn how to invoke functions by using both positional and keyword arguments. You will next work with positional input arguments in custom functions, and learn that these are required arguments, and how to order these arguments to invoke your function. You will next learn to use variable length arguments in defining custom functions. Finally, you will learn how keyword arguments or named arguments are a way to make the intent behind function invocation absolutely explicit, and help prevent bugs in programs that are especially hard to detect.
Perks of Course
Certificate: Yes
CPD Points: 123
Compliance Standards: AICC