366 Courses

With the rise of machine learning applications in recent years, demand for python programmers continues to grow correspondingly.

This course is designed for beginner-level students to create their first voice assistant in Python. If you have the questions: How to create a chatbot in Python? How to build a virtual assistant with Python? Then you are on the right course. This is a great small project to get you started (even if you have little or no prior knowledge in python) and a learning opportunity.

Duration 4 Days 24 CPD hours This course is intended for DevOps engineers Integration engineers Network and software architects Network engineers Software engineers System administrators Overview After completing this course, you should be able to: Describe network and IT convergence Describe Cisco NSO architecture Describe Linux Configure Cisco NSO Set up access control to Cisco NSO system Describe Cisco NSO Integration Options Explain version control systems and basic git concepts Describe the purpose of continuous integration and continuous delivery Implement Cisco NSO high availability Describe scalable system management Describe software development methodologies Describe service maintenance Perform NED upgrades Use Cisco NSO for managing services and their associated device configurations Describe Cisco NSO change management Explain service problem management Use Cisco NSO for service monitoring and compliance reporting Describe Cisco NSO inventory management Describe Cisco NSO use cases The Cisco Network Services Orchestrator (NSO) Administration and DevOps (NSO303) v4.0 course continues the learning journey of the NSO Essentials for Programmers and Network Architects (NSO201) v4.0 and NSO Advanced for Python Programmers (NSO300) v4.0 courses by introducing you to the system administration and DevOps focusing on NSO; the robust bridge linking network automation and orchestration tools, examining the development, operation, and administration task functions. You will learn how to set up, configure, deploy, and maintain a Cisco Network Services Orchestrator solution, and learn best practices for using DevOps. The examples shown in this course demonstrate real-world scenarios to prepare you for deployment and management of new or existing NSO instances. The course guides you through the setup of a production ready NSO instances using system installation with access control settings, the deployment of NSO in Docker containers, and introduces modern DevOps concepts and tools such as Git and Continuous Delivery/Continuous Deployment (CI/CD). You will learn how to migrate CDM devices, how to build NETCONF NEDs from the NSO CLI, how to handle NSO Alarms, and many more features that benefit you in your journey with Cisco NSO. Course Outline Introducing Network and IT Convergence Introducing Cisco NSO Architecture Introducing Linux Explaining Cisco NSO Setup Exploring Access Control Describing Integration Options Explaining Version Control System Describing Continuous Integration and Continuous Delivery Introducing Scalability and High Availability Describing Scalable System Management Describing Software Development Methodologies Introducing Service Maintenance Performing Network Element Driver (NED) Upgrades Introducing Configuration Management Describing Change Management Explaining Service Problem Management Explaining Service Monitoring and Compliance Reporting Introducing Inventory Management Describing Cisco NSO Use Cases

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create data-driven applications. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution. Python© continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Lesson 2: Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Lesson 3: Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Lesson 4: Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Lesson 5: Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Lesson 6: Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Lesson 7: Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Lesson 8: Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create data-driven applications. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution. Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Lesson 2: Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Lesson 3: Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Lesson 4: Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Lesson 5: Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Lesson 6: Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Lesson 7: Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Lesson 8: Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create a data-driven application. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution.   Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files Additional course details: Nexus Humans Advanced Programming Techniques with Python training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Advanced Programming Techniques with Python course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.