989 Python courses

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Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods Course Summary Lab outline Execute Your First Python Program Use the Python Interactive Shell Explore Foundation Python Data Types Explore Complex Python Data Types Use Standard String Operations Use Basic Pattern Matching Reformat MAC Addresses Use the if-else Construct Use for Loops Use while Loops Create and Use Functions Create and Use Classes Use the Python main() Construct Traverse the File Structure Read Data in Comma-Separated Values (CSV) Format Read, Store, and Retrieve Data in XML Format Read, Store, and Retrieve Date in JavaScript Object Notation (JSON) Format Read, Store, and Retrieve Data in a Raw or Unstructured Format Import Modules from the Python Standard Library Import External Libraries Create a Python Module Prompt the User for Input Use Command-Line Arguments Manage Exceptions with the try-except Structure Manage Exceptions with the try-except-finally Structure Use Assertions Use Simple Debugging Methods Use the Python Debugger Code a Practical Debugging Script

For pupils aged 9 - 16 | Delivered in UK Schools by Real World App and Games Developers Our micro:bit Workshop teaches your class about the micro:bit, making some apps and games with them during the workshop (we bring our own micro:bits too if your school doesn't yet have any!). We’ll introduce them to MakeCode, the coding language that the micro:bit uses, and teach them the fundamentals of coding before we work on some really fun projects! For older students, we can even use Python with the micro:bit!

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Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course Outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods

The goal of this course is to teach you how to deploy machine learning models in Flask. You'll also learn to deploy applications to the web. You'll learn to train your models, test them, and ensure that they are of the best quality.

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course Outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods Course Summary

Regular expressions training course description Regular expressions are an extremely powerful tool for manipulating text and data. They are now standard features in a wide range of languages and popular tools, including Python and MySQL. Regular expressions allow you to code complex and subtle text processing that you never imagined could be automated. Once you've mastered regular expressions, they'll become an invaluable part of your toolkit. You will wonder how you ever got by without them. What will you learn Use Regular Expressions. Troubleshoot Regular Expressions. Compare RE features among different versions. Explain how the regular expression engine works. Optimize REs. Match what you want, not what you don't want. Regular expressions training course details Who will benefit: Anyone looking to use regular expressions. Prerequisites: None. Duration 1 day Regular expressions training course contents Introduction to Regular Expressions Solving real problems, REs as a language, the filename analogy, language analogy, RE frame of mind, searching text files: egrep, egrep metacharacters, start and end of the line, character classes, matching any character with dot, alternation, ignoring differences in capitalization, word boundaries, optional items, other quantifiers: repetition, parentheses and backreferences, the great escape, expanding the foundation, linguistic diversification, the goal of a RE, more examples, RE nomenclature, Improving on the status quo. Extended introductory examples A short introduction to Perl, matching text with regular expressions, toward a more real-world example, side effects of a successful match, Intertwined regular expression, intermission, modifying text with regular expressions, example: form letter, example: prettifying a stock price, automated editing, a small mail utility, adding commas to a number with lookaround, text-to-HTML conversion, that doubled-word thing. Regular expression features and flavours The regex landscape, origins of REs, care and handling of REs, Integrated handling, procedural and object-oriented handling, search-and-replace example. strings character encodings and modes, strings as REs, character-encoding issues, unicode, regex modes and match modes, common metacharacters and features, character representations, character classes and class-like constructs, anchors and other 'zero-width assertions', comments and mode modifiers, grouping capturing conditionals and control. The mechanics of expression processing Two kinds of engines, new standards, regex engine types, from the department of redundancy department, testing the engine type, match basics, about the examples, rule 1: the match that begins earliest wins, engine pieces and parts, rule 2: the standard quantifiers are greedy, regex-directed versus text-directed, NFA engine: regex-directed, DFA engine: text-directed, first thoughts: NFA and DFA in comparison, backtracking, two important points on backtracking, saved states, backtracking and greediness, more about greediness and backtracking, problems of greediness, multi-character 'quotes', lazy quantifiers, greediness and laziness, laziness and backtracking, possessive quantifiers and atomic grouping, possessive quantifiers ?, +, *+, ++ and {m,n}+, the backtracking of lookaround, is alternation greedy? taking advantage of ordered alternation, NFA DFA and posix, the longest-leftmost', posix and the longest-leftmost rule, speed and efficiency. Practical regex techniques Continuation lines, matching an IP address, working with filenames, matching balanced sets of parentheses, watching out for unwanted matches, matching delimited text, knowing your data and making assumptions, stripping leading and trailing whitespace, matching and HTML tag, matching an HTML link, examining an HTTP URL, validating a hostname, plucking a hostname, plucking a URL, parsing CSV files. Crafting an efficient expression Efficiency vs. correctness, localizing greediness, global view of backtracking, more work for POSIX NFA, work required during a non-match, being more specific, alternation can be expensive, benchmarking, know what you re measuring, benchmarking with Python, common optimisations, the mechanics of regex application, pre-application optimizations, optimizations with the transmission, optimization of the regex itself, techniques for faster expressions, common sense techniques, expose literal text, expose anchors, lazy versus greedy: be specific, split into multiple REs, mimic initial-character discrimination, use atomic grouping and possessive quantifiers, lead the engine to a match, unrolling the loop, observations, using atomic grouping and possessive quantifiers, short unrolling examples, unrolling C comments, the free flowing regex, a helping hand to guide the match, a well-guided regex is a fast regex.

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