Pythonista - II (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
-
90 hours 5 minutesof self-paced video lessons -
53 Programscrafting your path to success -
Completion Certificateawarded on course completion
Functions in Python: Working with Advanced Features of Python Functions
Price on Request
1 hour 25 minutes
This course explores advanced Python function topics such as recursion, closures, and using generator functions to generate sequences. In 12 videos, you will learn how to use decorators to add functionality to code; examine how recursion can be used to construct code to solve complex problems; and learn to write a terminating condition for a recursive function. Next, you will learn how to use an Iterator to respond to a built-in next () function. Learners will also examine closures, and how as functions they maintain their own lexical environment; and explore how closures are functions that can yield dramatic results in the distributed processing of code, and are widely used in the implementation of distributed processing frameworks. Then you will learn how to use generator functions to generate sequences. You will learn how sequences can iterated upon by other parts of your program. Finally, you will learn that using decorators offers simple ways of invoking higher-order functions.
Perks of Course
Certificate: Yes
CPD Points: 86
Compliance Standards: AICC
Get Into Programming with Python Bootcamp: Session 1 Replay
Price on Request
2 hour 30 minutes
This is a recorded Replay of the Get Into Programming with Python Live session that ran on february 14th at 11 AM ET. In this session Axle Barr discusses variables, statements and expressions, variable types, casting, and the print command.
Perks of Course
Certificate: Yes
CPD Points: 152
Compliance Standards: AICC
Get Into Programming with Python Bootcamp: Session 2 Replay
Price on Request
2 hour 35 minutes
This is a recorded Replay of the Get Into Programming with Python Live session that ran on february 15th at 11 AM ET. In this session Axle Barr discusses decisions, flow charts, algorithms, compound statements, iteration, and for and while loops.
Perks of Course
Certificate: Yes
CPD Points: 153
Compliance Standards: AICC
Get Into Programming with Python Bootcamp: Session 3 Replay
Price on Request
2 hour 30 minutes
This is a recorded Replay of the Get Into Programming with Python Live session that ran on February 16th at 11 AM ET. In this session Axle Barr discusses arrays, array elements and positioning, iterating, and array functions.
Perks of Course
Certificate: Yes
CPD Points: 151
Compliance Standards: AICC
Get Into Programming with Python Bootcamp: Session 4 Replay
Price on Request
2 hour 35 minutes
This is a recorded Replay of the Get Into Programming with Python Live session that ran on February 17th at 11 AM ET. In this session Axle Barr discusses functions, parameters and arguments, syntax and logic errors, and object oriented programming.
Perks of Course
Certificate: Yes
CPD Points: 153
Compliance Standards: AICC
Getting Started with Python: Introduction
Price on Request
1 hour 30 minutes
This 15-video course lets learners explore the basics of how to use the Python programming language. You will learn to set up with an interactive environment that allows you to develop and run Python scripts on your machine. Begin by installing Anaconda, an open-source distribution of the Python and R programming languages. You will learn to write your first meaningful program in Python, then create a Jupyter notebook, the most popular tool for writing and running Python code. You will learn how to do simple coding by using Python's Jupyter notebooks, and explore different Jupyter functionalities, including built-in functions. Learners will explore how to use a Python variable to store values, and learn to differentiate between variables of different types, and the different ways to assign values to variables. You will examine how variables act as containers, and you will learn how to change values that are inside a container. Finally, you will learn to use integers, floating-point numbers, strings, and to work with Boolean values.
Perks of Course
Certificate: Yes
CPD Points: 89
Compliance Standards: AICC
Machine Learning in Python Bootcamp: Session 1 Replay
Price on Request
2 hour 40 minutes
This is a recorded Replay of the Machine Learning in Python Live session that ran on August 9th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 158
Compliance Standards: AICC
Machine Learning in Python Bootcamp: Session 2 Replay
Price on Request
2 hour 25 minutes
This is a recorded Replay of the Machine Learning in Python Live session that ran on August 10th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 145
Compliance Standards: AICC
Machine Learning in Python Bootcamp: Session 3 Replay
Price on Request
1 hour 40 minutes
This is a recorded Replay of the Machine Learning in Python Live session that ran on August 11th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 98
Compliance Standards: AICC
Machine Learning in Python Bootcamp: Session 4 Replay
Price on Request
1 hour 45 minutes
This is a recorded Replay of the Machine Learning in Python Live session that ran on August 12th at 11 AM ET.
Perks of Course
Certificate: Yes
CPD Points: 105
Compliance Standards: AICC
New Developments in Python
Price on Request
45 minutes
Python is an easy to learn, easy to read programming language widely used in scripting and application development. It's flexible and interpretive nature provides immediate feedback to users, making it one of the most popular programming languages today. Explore the roots of the Python language and discover its significant features. Examine the differences between versions 2 and 3 of Python and the process of migrating to the newer version. Delve into the new features that have been packed into subsequent releases of Python 3 and see how these can be adopted to build better applications. Finally, learn some of the best practices when it comes to building applications with Python - from the right syntax to improve readability to making your code easy to extend.
Perks of Course
Certificate: Yes
CPD Points: 46
Compliance Standards: AICC
NLP for ML with Python: Advanced NLP Using spaCy & Scikit-learn
Price on Request
40 minutes
This 11-video course explores NLP (natural language processing) by discussing differences between stemming, a process of reducing a word to its word stem, and lemmatization, or returning the base or dictionary form of a word. Key concepts covered here include how to extract synonyms, antonyms, and topic, and how to process and analyze texts for machine learning. You will learn to use Apache's Natural Language Toolkit (NLTK), spaCy, and Scikit-learn to implement text classification and sentiment analysis. This course demonstrates the use of advanced calculus and discrete optimization to implement robust and high-performance machine learning applications. You will learn to use R and Python to implement multivariate calculus for machine learning and data science, then examine the role of probability, variance, and random vectors in implementing machine learning processes and algorithms. Finally, you will examine the role of calculus in deep learning; watch a demonstration of how to apply calculus and differentiation using R and Python libraries; see how to implement calculus, derivatives, and integrals using Python; and learn uses of limits and series expansions in Python.
Perks of Course
Certificate: Yes
CPD Points: 40
Compliance Standards: AICC
NLP for ML with Python: NLP Using Python & NLTK
Price on Request
1 hour 30 minutes
This course explores how natural language processing (NLP) is used for machine learning, and examines the benefits and challenges of NLP when creating an application that can essentially understand human language. In its 13 videos, learners will be shown the essential components of NLP, including parsers, corpus, and corpus linguistic, as well as how to implement regular expressions. This course goes on to examine tokenization, a way to separate a piece of text into smaller units, and then illustrates different tokenization use cases with NLTK (Natural Language Toolkit). You will learn to use stop words using libraries and the NLTK. This course demonstrates how to implement regular expressions in Python to build NLP-powered applications. Learners will examine the list of Python NLP libraries along with their essential capabilities, including NLTK, Gensim, CoreNLP, spaCy and PyNLPl. You will learn to set up and configure an NLTK environment to illustrate how to process raw text. Finally, this course demonstrates the use of filtering stopwords in a tokenized sentence using NLTK.
Perks of Course
Certificate: Yes
CPD Points: 61
Compliance Standards: AICC
Python Best Practices Bootcamp: Session 1 Replay
Price on Request
2 hour 30 minutes
This is a recorded Replay of the Python Best Practices Live session that ran on March 22nd at 11 AM ET. In this session Joris Hoendervangers discusses Python tools and conventions, "Pythonic" code, and The Standard Library.
Perks of Course
Certificate: Yes
CPD Points: 151
Compliance Standards: AICC
Python Best Practices Bootcamp: Session 2 Replay
Price on Request
2 hour 10 minutes
This is a recorded Replay of the Python Best Practices Live session that ran on March 23rd at 11 AM ET. In this session Joris Hoendervangers discusses Virtual environments, Unit testing, and Type hints.
Perks of Course
Certificate: Yes
CPD Points: 130
Compliance Standards: AICC
Python Best Practices Bootcamp: Session 3 Replay
Price on Request
1 hour 50 minutes
This is a recorded Replay of the Python Best Practices Live session that ran on March 24th at 11 AM ET. In this session Joris Hoendervangers discusses Object Oriented Programming (OOP), Best practices, and dataclasses.
Perks of Course
Certificate: Yes
CPD Points: 110
Compliance Standards: AICC
Python Best Practices Bootcamp: Session 4 Replay
Price on Request
1 hour 55 minutes
This is a recorded Replay of the Python Best Practices Live session that ran on March 25th at 11 AM ET. In this session Joris Hoendervangers discusses Python in production, Intermediate concepts, and Tips & tricks.
Perks of Course
Certificate: Yes
CPD Points: 116
Compliance Standards: AICC
Python Classes & Inheritance: Advanced Functionality Using Python Classes
Price on Request
1 hour 30 minutes
Examine the advanced features that you can implement by using classes in Python, such as special methods, iterators, class properties, and abstract base classes. Key concepts covered in this 14-video course include how to represent objects by using customized strings; performing addition operations on custom objects; and performing subtraction operations on custom objects. Next, observe how to perform multiplication operations on custom objects and perform floor division, modulo, and power-of operations. Then study learn built-in functions to work with custom data types; learn to execute for-loops on custom data types; and learn about properties on classes for intuitive use. Learn about properties using a simpler syntax; work with class methods to access and update class state; work with utility methods on classes; and learn how to use the abstract method to make classes that are not instantiable base classes. Finally, learners will be shown special methods and what they represent; learn to define a class and create a property within it; and observe how to differentiate between class methods and static methods.
Perks of Course
Certificate: Yes
CPD Points: 88
Compliance Standards: AICC
Python Classes & Inheritance: Getting Started with Classes in Python
Price on Request
1 hour 35 minutes
Explore implementations of Python classes, methods, and instance and class variables in this 15-video course. Learn how to implement private variables in Python classes and program problems with classes. Key concepts covered here include how to create classes by using Python; how to assign attributes to objects of classes; and how to initialize class variables by using the init special method. Next, you will observe how to initialize values for a class when you create objects; how to pass arguments to initialize the state of a class object; and additional methods in a class, as well as how class variables work. Learners will examine how class variables are different from instance variables and how class variables share memory across objects of a class; and work with variables that have their own memory in each object. Then examine getters and setters for each instance variable; learn to prevent inadvertent modification of instance variables; and learn to create a class to represent a real-world entity. Finally, observe how to parse information to create classes with a dictionary.
Perks of Course
Certificate: Yes
CPD Points: 93
Compliance Standards: AICC
Python Classes & Inheritance: Introduction
Price on Request
50 minutes
In this 7-video course, learners will explore the concept of logical units, such as classes, and how they are used to hold state and behavior. Examine the modeling of is-a relationships by using inheritance and the advantages of object-oriented programming. You will begin with an introduction to classes, which are an integral part of Python programming. In this first tutorial, learn how state and behavior can be encapsulated in a single unit. This leads learners to examine how classes can be used as blueprints to create objects, and then to compare objects and instances to classes. Following on from this, you will take a look at inheritance, and model is-a relationship using inheritance. In the final tutorial in this course, you will explore the advantages of using object-oriented programming. In the concluding exercise, you will be asked to describe classes, define how state and behavior of a class are represented, list characteristics of class objects or instances, describe class inheritance, and list advantages of object-oriented programing with classes.
Perks of Course
Certificate: Yes
CPD Points: 49
Compliance Standards: AICC
Python Classes & Inheritance: Working with Inheritance in Python
Price on Request
1 hour 10 minutes
In this 12-video course, learners will discover how to implement inheritance by using Python classes and explore coding examples of concepts such as base classes, derived classes, overriding methods, and polymorphism. Key concepts covered in this course include the default base class for all Python classes; how to model an is-a relationship by using inheritance; and how to invoke base class methods from subclasses. Next, you will observe how to define implementations for base class methods; learn to work with superclass and subclass hierarchies; and learn to define methods in a subclass and the idea of subclasses having additional attributes. Continue by learning about multiple inheritance levels in classes; multiple base classes for a single subclass; and polymorphism, an important characteristic of objects in object-oriented programming. Then you will learn to implement polymorphism in Python; learn about class inheritance and polymorphism; and learn to implement base and derived classes. Finally, learn to specify an init method to initialize member variables; learn about getters and setters for member variables; and learn to override a method.
Perks of Course
Certificate: Yes
CPD Points: 69
Compliance Standards: AICC
Python Concurrent Programming: Asynchronous Executions in Python
Price on Request
1 hour 30 minutes
This 9-video course offers a lab-only exploration and introduction to the libraries available in Python to run tasks asynchronously by using both processes and threads. To take this course, you should have prior knowledge of how to spawn and manage processes in Python. First, you will learn how to significantly improve the performance and responsiveness of your application by running them concurrently, then learn how to create a process pool, and how to use multiprocessing to execute tasks in parallel. Next, you will learn to use multithreading to run chunks of a task at one time, and to switch between the chunks regularly. Learners will then examine the concurrent.futures module, which contains objects to run threads and processes in an asynchronous manner, and to monitor their progress while they are still executing. Continue by learning how to use ThreadPoolExecutor, available in the concurrent.futures module. Finally, you examine the asyncio module in Python, which provides lightweight mechanisms for asynchronous executions of tasks.
Perks of Course
Certificate: Yes
CPD Points: 61
Compliance Standards: AICC
Python Concurrent Programming: Introduction to Concurrent Programming
Price on Request
1 hour 30 minutes
Explore the general theory of concurrent programming, and examine how to have multiple tasks active at any given point in time. This 14-video course offers an in-depth examination of concurrent programming by using the Python programming language. First, learners will examine the two main forms of concurrent programming, multithreading and multiprocessing, and examine their differences and use cases. Next, you will examine executing multitask sequentially, and with multithreading to save time, and how to use multiprocessing to manage a collection of tasks efficiently. Continue by exploring challenges that programmers encounter when adopting concurrency such as synchronization issues and deadlocks, and how to address these issues. You will examine issues that arise when writing concurrent code, and you will learn how to fix these by using the built-in objects available in Python. Finally, this course examines several of the objects available in the Python language such as queues and pools, which simplify the task of building multithreading and multiprocessing applications.
Perks of Course
Certificate: Yes
CPD Points: 89
Compliance Standards: AICC
Python Concurrent Programming: Multiprocessing in Python
Price on Request
1 hour 15 minutes
This course is a lab-only exploration of the creation and management of processes in Python to speed up the execution of your programs. In this 10-video course, learners will use Jupyter notebooks to execute all programs demonstrated. First, you will learn how to create initialized threads, and how to do the same with processes in Python. Then you will examine different thread-safe data structures in Python to implement queues, stacks, and priority queues. Next, you will learn how to use Python for synchronization mechanisms and inter-process communication, and will see a comparison of processes to threads. You will learn to use Python's built-in queue data structure for multithreaded applications, and how to implement multiprocessing. Continue by learning how processes are created and executed and how they differ from threads when one is using shared resources. You will explore how to use a manager class, or service process manager to share any Python types. Finally, you will examine the available mechanisms in Python for communication and synchronization between processes.
Perks of Course
Certificate: Yes
CPD Points: 76
Compliance Standards: AICC
Python Concurrent Programming: Multithreading in Python
Price on Request
1 hour 40 minutes
This course offers an in-depth exploration of the creation and management of concurrent threads in Python. In its 14 videos, you will learn how to significantly improve the performance and responsiveness of your apps by using concurrent threads. Begin by examining how threads are created in Python from their initialization to their execution; then learn how to use the various synchronization mechanisms such as locks, semaphores, and events. Next, you will examine how concurrent execution could occur in two ways: multithreading and parallel. You will learn to use multithreading to run chunks of each task at one time, and then switch between them regularly. You will learn multiprocessing of threads by executing tasks in parallel. Learners will examine concurrent execution of threads, and some of the issues that arise when these threads are not synchronized. Finally, you will examine several threads of synchronization mechanisms available in Python such as locks, semaphores, events, and conditions and explore the properties and use cases for each of these objects.
Perks of Course
Certificate: Yes
CPD Points: 101
Compliance Standards: AICC
Python Design Patterns: Principles of Good Design
Price on Request
1 hour 35 minutes
Explore how the SOLID principles can help to make software designs easier to understand and maintain for Python developers. In this 14-video course, learners will examine the five SOLID principles-Single Responsibility, Open/Closed, Liskov's Substitution, Interface Segregation, and Dependency Inversion-as well as creational, structural, and behavioral design patterns. Key concepts covered here include the basic principles of good design in code; learning the Single Responsibility and Open/Closed principles of good design; and learning the Liskov's Substitution, Interface Segregation, and Dependency Inversion principles of good design. Next, learners will examine the principle of Least Knowledge and the Hollywood principle of good design; examine issues that may arise when classes do not implement the principle of Single Responsibility; and observe how to implement the principles of Single Responsibility and Open/Closed. Continue by learning how to design and implement the Liskov's Substitution principle, the Interface Segregation principle, and the Dependency Inversion principle. Finally, learners will study the three broad categories of design patterns and when to use each of them.
Perks of Course
Certificate: Yes
CPD Points: 94
Compliance Standards: AICC
Python Design Patterns: Working with Behavioral Design Patterns
Price on Request
1 hour 25 minutes
Explore the design and implementation of five commonly used behavioral design patterns: Strategy, Chain of Responsibility, Observer, Command, and Iterator. Examine how these patterns can be used in Python built-in functions, in simple and complex use cases, for performing undo operations, and with Python special methods. Key concepts covered in this course include the Strategy pattern, how to design and implement the pattern, and how it is used in Python built-in functions; and learning the Chain of Responsibility pattern and how to write code to implement the pattern. Next, you will learn about the Observer pattern and how to implement the pattern for a simple use case and how to implement the pattern for a more complex use case. Finally, learners will study the Command pattern and how to implement the pattern to perform undo operations; and learn the Iterator pattern and its applications and learn to design an Iterator by using special methods in Python.
Perks of Course
Certificate: Yes
CPD Points: 86
Compliance Standards: AICC
Python Design Patterns: Working with Creational Design Patterns
Price on Request
1 hour 30 minutes
In this 16-video course, learners will explore the details and implementation of five commonly used creational design patterns: Singleton, Factory, Abstract Factory, Builder, and Object Pool. Key concepts covered here include how the Singleton pattern works and when to use it; how to write code for a simple implementation of the Singleton pattern; and how to implement the Singleton pattern by using a more Pythonic style and global objects in Python. Next, learn how the Factory and Abstract Factory patterns work; how to iteratively improve the design of code using refactoring; and how to design and implement the serializer with the Factory pattern. Continue by learning how to apply the Abstract Factory pattern to create a family of objects; how the Builder pattern works and how to implement a simple design for the Builder pattern; and how the Object Pool pattern works and how to implement the Object Pool pattern to limit the number of instances. Finally, learn how to improve the Object Pool pattern by making the object pool a singleton.
Perks of Course
Certificate: Yes
CPD Points: 108
Compliance Standards: AICC
Python Design Patterns: Working with Structural Design Patterns
Price on Request
1 hour 25 minutes
Explore the design and implementation of five commonly used structural Python design patterns: Adapter, Decorator, Facade, Proxy, and Flyweight. In this 14-video course, learners examine how these patterns can be used for tasks such as working with legacy components, dynamically adding responsibilities, offering a simple client interface, controlling object access, and efficiently using lightweight resources. Key concepts covered here include design of the Adapter pattern and need for the pattern when working with legacy components; learning how to write code for the Adapter pattern to offer a consistent interface to clients; and learning design of the Decorator pattern and the importance for adding responsibilities dynamically. Continue by observing how to implement the Decorator pattern to allow adding responsibilities at runtime. Next, you will learn about the design of the Façade pattern and implementing the pattern to offer a simple interface to clients; learn to design and implement the Proxy pattern to control access to an object; and learn the design of the Flyweight pattern and how to implement the pattern to efficiently use lightweight resources.
Perks of Course
Certificate: Yes
CPD Points: 86
Compliance Standards: AICC
Python Development: Defining, Configuring, & Invoking Functions
Price on Request
1 hour 45 minutes
In Python, functions are essentially first-class citizens. They are objects in Python, just like other primitive and complex data types, and have a valuable purpose. In this course, you'll learn how to define and invoke functions in Python. First, you'll define a function using the def keyword and specify input arguments and return values from functions. You'll then work with positional arguments and keyword arguments. Next, you'll define functions with default values for arguments and a variable number of arguments. Along the way, you'll also examine how arguments can be pass-by-value or pass-by-reference. Finally, you'll explore the characteristics of Python functions that make them first-class citizens. When you're finished with this course, you'll have a solid grasp of the foundations of support for functions in Python and be able to use Python functions in your development work.
Perks of Course
Certificate: Yes
CPD Points: 104
Compliance Standards: AICC
Python Development: Getting Started with Programming in Python
Price on Request
1 hour 30 minutes
Python is a beneficial language for use in a lot of development projects, particularly Java/C++ development. In this course, you'll learn the basics of Python programming. You'll start by installing Python on your local machine and practice writing code using the Python shell. Next, you'll perform basic math and logical operations in Python. You'll create Python variables and see how you can assign and access values stored in these variables. You'll then use built-in functions, which are part of the core Python programming language, to perform simple calculations and operations. Finally, you'll explore strings in Python work, creating strings using single, double, and triple quotes depending on the use case. You'll then briefly examine the use of complex data types, such as lists, tuples, sets, and dictionaries. When you're finished with this course, you'll be able to execute simple Python commands on Jupiter notebooks.
Perks of Course
Certificate: Yes
CPD Points: 88
Compliance Standards: AICC
Python Development: Performing Operations with Complex Data Types
Price on Request
1 hour 55 minutes
All values in Python are classified into data types. One of these, known as complex data types, facilitates using complex numbers. In this course, you'll learn how to work with complex data types in Python. You'll start by exploring the list data type, which contains an ordered collection of elements. You'll then perform several different operations on lists, such as accessing, adding, and removing elements and implementing slicing operations. Next, you'll work with tuples and examine how tuples contain an ordered collection of elements but are immutable in nature. You'll also work with sets and dictionaries. Finally, you'll explore the nuances of the copy operation for complex data types. When you're finished with this course, you'll be able to use the right Python data type to store your data and perform basic operations using these complex data types.
Perks of Course
Certificate: Yes
CPD Points: 114
Compliance Standards: AICC
Python Development: Working with If Statements, Loops, & Comprehensions
Price on Request
1 hour 45 minutes
A handy procedure in Python for controlling the execution order of program statements is to implement branching operations using conditional statements, such as 'if' and 'else'. In this course, you'll learn how to use statements, loops, and comprehensions. First, you'll implement the conditional if statement. Then you'll use the else and elif statements. Moving on, you'll use Python's looping constructs, including the for-loop to iterate over elements in complex data types as well as over lists, tuples, and dictionaries. You'll use the while-loop and the break, continue, and pass keywords to further control loop execution. Finally, you'll implement list comprehension in Python, an elegant and efficient way of generating lists using 'for loops.' When you're finished with this course, you'll be able to write conditional statements in your code and perform looping and branching operations using for and while loops.
Perks of Course
Certificate: Yes
CPD Points: 105
Compliance Standards: AICC
Python for DevOps Bootcamp: Session 1 Replay
Price on Request
2 hour
This is a recorded Replay of the Python for DevOps Live session that ran on March 30th at 11 AM ET.In this session Noah Gift discusses Python for DevOps and Automating Text and Filesystems.
Perks of Course
Certificate: Yes
CPD Points: 119
Compliance Standards: AICC
Python for DevOps Bootcamp: Session 2 Replay
Price on Request
2 hour
This is a recorded Replay of the Python for DevOps Live session that ran on March 31st at 11 AM ET. In this session Noah Gift discusses Developing with the Command Line and Continuous Integration and Delivery.
Perks of Course
Certificate: Yes
CPD Points: 118
Compliance Standards: AICC
Python Fundamentals Bootcamp: Session 1 Replay
Price on Request
3 hour 5 minutes
This is a recorded Replay of the Python Fundamentals Live session that ran on October 19th at 11 AM ET. In this session Joris Hoendervangers introduces Jupyter Notebooks, variabes, keywords, data types, and print statements.
Perks of Course
Certificate: Yes
CPD Points: 185
Compliance Standards: AICC
Python Fundamentals Bootcamp: Session 2 Replay
Price on Request
2 hour 35 minutes
This is a recorded Replay of the Python Fundamentals Live session that ran on October 20th at 11 AM ET. In this session Joris Hoendervangers discusses data types.
Perks of Course
Certificate: Yes
CPD Points: 155
Compliance Standards: AICC
Python Fundamentals Bootcamp: Session 3 Replay
Price on Request
3 hour
This is a recorded Replay of the Python Fundamentals Live session that ran on October 21st at 11 AM ET. In this session Joris Hoendervangers discusses flow control.
Perks of Course
Certificate: Yes
CPD Points: 179
Compliance Standards: AICC
Python Fundamentals Bootcamp: Session 4 Replay
Price on Request
2 hour 40 minutes
This is a recorded Replay of the Python Fundamentals Live session that ran on October 22nd at 11 AM ET. In this session Joris Hoendervangers discusses functions and modules.
Perks of Course
Certificate: Yes
CPD Points: 159
Compliance Standards: AICC
Python Requests: HTTP Requests with Python
Price on Request
1 hour 40 minutes
Learners can explore how to use the Python Request package which has simplified the task of constructing HTTP requests in this 16-video lab course, which explores different types of HTTP requests, and examines several ways to handle responses to those requests. Begin by learning how to use the Python request package to make a GET request for data from a server. Then you will observe how to construct a POST request to submit data to a host, and how to send it to a URL. Continue by learning how to use a HEAD request to check the resource information before downloading it by using GET, and how to examine request and response headers. Next, learners will examine a PUT request which has the same effect whether one makes the request once or multiple times, and which is used to overwrite an existing resource. You will learn to use DELETE requests. Finally, you will learn to address responses to requests in both JSON formatted or images.
Perks of Course
Certificate: Yes
CPD Points: 102
Compliance Standards: AICC
Python Statistical Plots: Time Series Data & Regression Analysis in Seaborn
Price on Request
1 hour 35 minutes
Seaborn's smartly designed interface lets you illuminate data through aesthetically pleasing statistical graphics that are incredibly easy to build. In this course, you'll discover Seaborn's capabilities. You'll begin using strip plots and swarm plots and recognizing how they work together using low-intensity noise. You'll then work with time series data through various techniques, like resampling data at different time frequencies and plotting with confidence intervals and other types of error bars. Next, you'll visualize both logistic and linear regression curves. Moving on, you'll use the pairplot function to visualize the relationships between columns in your data, taken two at a time, in a grid format. You'll change the chart type being visualized and create pair plots with multiple chart types in each plot. Lastly, you'll create and format a heatmap of a correlation matrix to identify relationships between dataset columns.
Perks of Course
Certificate: Yes
CPD Points: 93
Compliance Standards: AICC
Python Statistical Plots: Visualizing & Analyzing Data Using Seaborn
Price on Request
1 hour 45 minutes
The wealth of Python data visualization libraries makes it hard to decide the best choice for each use case. However, if you're looking for statistical plots that are easy to build and visually appealing, Seaborn is the obvious choice. You'll begin this course by using Seaborn to construct simple univariate histograms and use kernel density estimation, or KDE, to visualize the probability distribution of your data. You'll then work with bivariate histograms and KDE curves. Next, you'll use box plots to concisely represent the median and the inter-quartile range (IQR) and define outliers in data. You'll work with boxen plots, which are conceptually similar to box plots but employ percentile markers rather than whiskers. Finally, you'll use Violin plots to represent the entire probability density function, obtained via a KDE estimation, for your data.
Perks of Course
Certificate: Yes
CPD Points: 106
Compliance Standards: AICC
Python Unit Testing: Advanced Python Testing Using the unittest Framework
Price on Request
1 hour 30 minutes
This 10-video course explores advanced features of Python testing uses of the unit-test Framework, and will examine several ways to optimize tests. A labs-only course using Linux Shell, it explores the unit-test framework, the pytest, and the doctest, and how to use them to automate the testing of all the functions in Python applications. You will learn how to bundle common operations for multiple tests into a special function or fixture, which make test scripts easier to view and maintain. Next, you will learn to adjust the scope of fixture functions to execute before each individual test, or to execute just once for the entire test case. Learners will examine how to create and execute a collection of test cases called test suites. You will explore the PyCharm IDE (integrated development environment), which includes support for several different testing frameworks. Finally, you will explore how PyCharm IDE simplifies the creation of tests by generating boilerplate code for test scripts with just a few clicks.
Perks of Course
Certificate: Yes
CPD Points: 60
Compliance Standards: AICC
Python Unit Testing: An Introduction to Python's unittest Framework
Price on Request
50 minutes
This 8-video course explores the unit-test framework in Python. To take this course, you should have experience in Python programming and the use of the Linux shell. The unit-test framework (also known as PyUnit) is modeled on JUnit and simplifies the automation of tests for Python applications. You will learn to use the unit-test framework to define tests for your application source code to ensure that it behaves in a specified manner. In this course, learners will write a sample test, and then expand the test scripts to include multiple tests. You will learn how to sequence the execution of tests in scripts, and how to filter out tests which do not require a specific run. Next, you will learn how to pass the output of test executions to identify the results of your tests, and how to diagnose test failures. You will learn how to run specific tests from among multiple tests in your scripts. Finally, this course demonstrates how to skip the execution of tests by using the skip decorator.
Perks of Course
Certificate: Yes
CPD Points: 50
Compliance Standards: AICC
Python Unit Testing: Testing Python Code Using doctest
Price on Request
45 minutes
This 8-video course explores several Python applications for testing, including the unit-test framework, pytest, and doctest. To take this course, you should have prior experience with Python programming, and familiarity with running commands from a Linux shell. This course focuses on doctests, and examines how the doctest module allows the definition of simple python tests within the docstrings in your source code. You will examine what syntax is needed when manually running tests from a Python shell, and how to copy over shells. Next, you will learn to capture the output and use it in your source file, then how to create an executable document for your source. This course demonstrates packaging a readme file, and the tests for a Python module. Learners will examine the bundling of documentation and tests into a single executable file. You will learn how to Ellipsis directive to address unpredictable outputs. Finally, you will learn to instruct your doctests to ignore whitespace characters within the outputs of a test by using the normalized whitespace directive.
Perks of Course
Certificate: Yes
CPD Points: 43
Compliance Standards: AICC
Python Unit Testing: Testing Python Code Using pytest
Price on Request
1 hour 15 minutes
Explore several types of testing frameworks for Python applications, including the unittest framework, pytest, and doctest, in this 12-video course. First, you will learn how to define and run tests, and how to streamline tests by using fixtures. You will learn the important features of the pytest framework to create small test units, and to define and run individual tests. Next, you will learn to group tests into multiple scripts, and how to execute multiple test scripts within a single run. Learners will observe how to create a simple test, and learn to increase the complexity by defining test scripts to cover multiple tests for your application. You will explore the execution and skipping of specific tests in scripts, then learn to simplify tests by using parameterization. You will learn how to apply filters on different tests, and to execute tests with a certain string in the test name, and examine the use of markers in a test. Finally, you will learn how to use fixtures to run operations common to multiple tests.
Perks of Course
Certificate: Yes
CPD Points: 73
Compliance Standards: AICC
Python with Altair: An Introduction to Altair
Price on Request
50 minutes
This course will get you familiar with the building blocks of Altair visualizations and some of the important chart settings. You will touch upon some of the fundamentals of plotting graphs in Altair. You'll start off by learning about the basic data structures that can form the basis of Altair visualizations, including JSON data and Pandas DataFrames in both wide-form and long-form. You'll then move on to plotting one of the simpler graphs, histograms, to visualize the distribution of values for a quantitative field in your dataset. While doing so, you'll get to explore the different ways in which Altair graphs can be customized including augmenting your chart with text, layering histograms to view two distributions together, and making histograms interactive.
Perks of Course
Certificate: Yes
CPD Points: 52
Compliance Standards: AICC
Python with Altair: Plotting Fundamental Graphs
Price on Request
1 hour 40 minutes
This course will introduce you to a breadth of charts available in Altair and how you can use them to get an all-round understanding of your data. The focus is to get you familiar with the wide variety of graphs that are available. You'll begin by visualizing a distribution of numeric values using box plots and violin charts, each of which has its own strengths and limitations when analyzing distributions. You'll then move on to bar charts to analyze numbers associated with categories in your data. While doing so, you will get to explore a variety of aggregate operations that are available in Altair in order to calculate a sum, mean, median, and so on. You'll then use line charts to visualize the changes in a particular value over a period of time and also its related visual - the area chart. Finally, you'll produce scatter plots to visualize the relationship between a pair of fields in your data. Throughout this course, you'll delve into a number of customizations which are available in Altair for each of the graphs which you plot.
Perks of Course
Certificate: Yes
CPD Points: 98
Compliance Standards: AICC
Python with Altair: Working with Specialized Graphs
Price on Request
1 hour 30 minutes
This course introduces you to the use of Altair visualizations which can convey very detailed information for specialized datasets. You will cover some of the graphs that can be used to convey the information in very specific kinds of datasets, while also giving you some hands-on experience with advanced chart configurations. You'll begin by plotting information on a map, both to mark locations of places as well as to convey numerical information about regions. You'll then build a heatmap to analyze the numbers associated with a combination of two categorical variables. Next, you'll implement candlestick charts to visualize stock price movements, dot plots to analyze the range of movement for some values, and Gantt charts to view a project plan. Finally, you'll explore the use of window functions to analyze the top K elements in each category of your dataset.
Perks of Course
Certificate: Yes
CPD Points: 91
Compliance Standards: AICC
Selenium Deep Dive: Managing Data Elements Using Python & Selenium
Price on Request
45 minutes
To become proficient in automated testing and an expert Selenium user, you need to know how to work with Selenium RC Server and Python to execute tests and manage various data elements. In this course, you'll learn to work with Selenium RC Server and Selenium Python RegEx to automate testing on various web application components to extract email addresses, phone numbers, href elements, and texts from images. You'll also learn to verify Javascript code execution and implement the Python exception logging module. Next, you'll learn how to automate low-level mouse interactions using Selenium Python and the ActionChains class. You'll utilize WebDriver's conditional commands using Selenium Python, to automate tests. Finally, you'll use Selenium Python and the ""By class"" locator to fetch all available attributes.
Perks of Course
Certificate: Yes
CPD Points: 47
Compliance Standards: AICC
Socket Programming in Python: Advanced Topics
Price on Request
1 hour 20 minutes
This 11-video course explores advanced features of Python sockets, including the transfer of large files over sockets, two-way communication, and differences between blocking and nonblocking sockets. You will learn to transfer large files over sockets by breaking them up into chunks, and to transfer images over TCP (transmission control protocol) sockets. Then you will learn how to transfer Python objects by using the pickle module. Next, learn how to create a chat application and use it to transfer several types of data from a server application to a client. Learners continue by exploring how to configure two-way communication over sockets by building a simple chat. This course examines the performance versus reliability trade-off when one uses blocking and nonblocking sockets. You will examine and compare TCP, a connection-oriented protocol, and UDP (Universal Datagram Protocol) which is connectionless. Finally, you will examine the performance versus reliability trade-off with a TCP and UDP, and why TCP is better suited for apps which require high reliability at the other end of the communication line.
Perks of Course
Certificate: Yes
CPD Points: 80
Compliance Standards: AICC
Socket Programming in Python: Introduction
Price on Request
1 hour
Learners can explore basic concepts of Python socket programming, and how to communicate small amounts of data between Python applications by using either the same machine or over a network, in this 9-video course. Begin by learning how to use Python language to set up a communication line by creating a socket. Then learn to initialize a simple socket, and use it to transfer text data from one application to another. This course next demonstrates how to create a client app and server app in Python, and how each app uses a socket to communicate. Learners will observe a demonstration of how to transmit a Python dictionary and custom object over a socket connection. You will learn how to use a socket model to set up a simple TCP (transmission control protocol) socket to transfer text between applications. Next, learners will examine other properties of Python sockets, including its use with the context manager and the setting of a time-out for connections. Finally, you will learn to use the Pickle library to convey Python objects over a socket connection.
Perks of Course
Certificate: Yes
CPD Points: 62
Compliance Standards: AICC
Support Vector Machine (SVM) Math: Building & Applying SVM Models in Python
Price on Request
1 hour 35 minutes
Support vector machines (SVMs) are a popular tool for machine learning enthusiasts at any level. They offer speed and accuracy, are computationally uncomplicated, and work well with small datasets. In this course, learn how to implement a soft-margin SVM classifier using gradient descent in the Python programming language and the LIBSVM library to build a support vector classifier and regressor. For your first task, generate synthetic data that can be linearly separated by an SVM binary classifier, implement the classifier by applying gradient descent, and train and evaluate the model. Moving on, learn how to use a pre-built SVM classifier supplied by the LIBSVM module. Then use LIBSVM to train a support vector regressor, evaluate it, and use it for predictions. Upon completion, you'll know how to work with custom SVM classifiers and pre-built SVM classification and regression models.
Perks of Course
Certificate: Yes
CPD Points: 94
Compliance Standards: AICC