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Complete Python training course description Python is an agile, robust, expressive, fully objectoriented, extensible, and scalable programming language. It combines the power of compiled languages with the simplicity and rapid development of scripting languages. This course covers Python from the very basics of 'hello world!' through to object oriented programming and advanced topics such as multi threading. Hands on follows all the major sections in order to reinforce the theory. What will you learn Read Python programs. Write Python programs. Debug Python programs. Use Python's objects and memory model as well as its OOP features. Complete Python programming training course details Who will benefit: Anyone wishing to learn Python. Prerequisites: None. Duration 5 days Complete Python programming training course contents Welcome to Python: What is Python? Origins, features. Downloading and installing Python, Python manuals, comparing Python, other implementations. Getting started: Program output, the print statement, "hello world!", Program input, raw_input(), comments, operators, variables and assignment, numbers, strings, lists and tuples, dictionaries, indentation, if statement, while Loop, for loop. range(), list comprehensions. Files, open() and file() built-in functions. Errors and exceptions. Functions, Classes, Modules, useful functions. Python basics: Statements and syntax, variable assignment, identifiers, basic style guidelines, memory management, First Python programs, Related modules/developer tools. Python Objects: Other built-in types, Internal Types, Standard type operators, Standard type built-in functions, Categorizing standard types, Unsupported types. Numbers: Integers, Double precision floating point numbers, Complex numbers, Operators, Built-in and factory functions, Other numeric types. Sequences: strings, lists, and tuples: Sequences, Strings, Strings and operators, String-only operators, Built-in functions, String built-in methods, Special features of strings, Unicode, Summary of string highlights, Lists, Operators, Built-in functions, List type built-in methods, Special features of lists, Tuples, Tuple operators and built-in functions, Tuples special features, Copying Python objects and shallow and deep copies. Mapping and set types: Mapping Type: dictionaries and operators, Mapping type built-in and factory functions, Mapping type built-in methods, Dictionary keys, Set types, Set type operators, Built-in functions, Set type built-in methods. Conditionals and loops: If, else and elif statements, Conditional expressions, while, for, break, continue and pass statements, else statement . . . take two, Iterators and iter(), List comprehensions, Generator expressions. Files and input/output: File objects, File built-in functions [open() and file()], File built-in methods and attributes, Standard files, Command-line arguments, File system, File execution, Persistent storage modules. Errors and exceptions: What are exceptions? Detecting and handling exceptions, Context management, Exceptions as strings, Raising exceptions, Assertions, Standard exceptions, Creating Exceptions, Why exceptions, Exceptions and the sys module. Functions: Calling, creating and passing functions, formal arguments, variable-length arguments, functional programming, Variable scope, recursion, generators. Modules: Modules and files, Namespaces, Importing modules, Module import features, Module built-in functions, Packages, Other features of modules. Object-Oriented Programming (OOP): Classes, Class attributes, Instances, Instance attributes, Binding and method invocation, Static methods and class methods, Composition, Sub-classing and derivation, Inheritance, Built-in functions for classes, and other objects, Customizing classes with special methods, Privacy, Delegation, Advanced features of new-style classes (Python 2.2+), Related modules and documentation. Execution environment: Callable and code Objects, Executable object statements and built-in functions, Executing other programs. 'Restricted' and 'Terminating' execution, operating system interface. Regular expressions: Special symbols and characters, REs and Python, Regular expressions example. Network programming: Sockets: communication endpoints, Network programming in Python, SocketServer module, Twisted framework introduction. Internet client programming: What are internet clients? Transferring files, Network news, E-mail. Multithreaded Programming: Threads and processes Python, threads, and the global interpreter lock, The thread and threading Modules. GUI programming: Tkinter and Python programming, Tkinter Examples, Brief tour of other GUIs. Web programming: Web surfing with Python: creating simple web clients, Advanced Web clients, CGI: helping web servers process client data, Building CGI applications, Using Unicode with CGI, Advanced CGI, Web (HTTP) Servers. Database programming: Python database application programmer's interface (DB-API), ORMs. Miscellaneous Extending Python by writing extensions, Web Services, programming MS Office with Win32 COM, Python and Java programming with Jython.

In this course, we will explore some features introduced recently in the language and a few important things that should be kept in mind while programming JavaScript. Learn some important JavaScript concepts and hacks to eliminate your fear of coding and improve your JavaScript coding skills. This course expects a fair understanding of JavaScript to start with.

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3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support

Advance your career in cloud computing with this carefully structured course on AWS CloudFormation. This course will equip you with all the necessary basic concepts such as writing CloudFormation templates, CloudFormation stacks, stack sets, nested stacks, puzzles, and much more.

If you’re looking to start a career in HTML & CSS coding, but don’t know where to begin, this might be for you. This course is aimed at absolute beginners that have never done any coding before. Early on in the course, you’ll learn what coding is, what certain types of languages are used for, specifically HTML & CSS, and the types of careers available through learning HTML & CSS.

Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug-fixing involved in creating and maintaining applications, frameworks, or other software components.

Python 3 is one of the most popular programming languages. Companies like Facebook, Microsoft, and Apple all want Python

Duration 5 Days 30 CPD hours Overview Mining data Manipulating data Visualizing and reporting data Applying basic statistical methods Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. 1 - Identifying Basic Concepts of Data Schemas Identify Relational and Non-Relational Databases Understand the Way We Use Tables, Primary Keys, and Normalization 2 - Understanding Different Data Systems Describe Types of Data Processing and Storage Systems Explain How Data Changes 3 - Understanding Types and Characteristics of Data Understand Types of Data Break Down the Field Data Types 4 - Comparing and Contrasting Different Data Structures, Formats, and Markup Languages Differentiate between Structured Data and Unstructured Data Recognize Different File Formats Understand the Different Code Languages Used for Data 5 - Explaining Data Integration and Collection Methods Understand the Processes of Extracting, Transforming, and Loading Data Explain API/Web Scraping and Other Collection Methods Collect and Use Public and Publicly-Available Data Use and Collect Survey Data 6 - Identifying Common Reasons for Cleansing and Profiling Data Learn to Profile Data Address Redundant, Duplicated, and Unnecessary Data Work with Missing Value Address Invalid Data Convert Data to Meet Specifications 7 - Executing Different Data Manipulation Techniques Manipulate Field Data and Create Variables Transpose and Append Data Query Data 8 - Explaining Common Techniques for Data Manipulation and Optimization Use Functions to Manipulate Data Use Common Techniques for Query Optimization 9 - Applying Descriptive Statistical Methods Use Measures of Central Tendency Use Measures of Dispersion Use Frequency and Percentages 10 - Describing Key Analysis Techniques Get Started with Analysis Recognize Types of Analysis 11 - Understanding the Use of Different Statistical Methods Understand the Importance of Statistical Tests Break Down the Hypothesis Test Understand Tests and Methods to Determine Relationships Between Variables 12 - Using the Appropriate Type of Visualization Use Basic Visuals Build Advanced Visuals Build Maps with Geographical Data Use Visuals to Tell a Story 13 - Expressing Business Requirements in a Report Format Consider Audience Needs When Developing a Report Describe Data Source Considerations For Reporting Describe Considerations for Delivering Reports and Dashboards Develop Reports or Dashboards Understand Ways to Sort and Filter Data 14 - Designing Components for Reports and Dashboards Design Elements for Reports and Dashboards Utilize Standard Elements Creating a Narrative and Other Written Elements Understand Deployment Considerations 15 - Understand Deployment Considerations Understand How Updates and Timing Affect Reporting Differentiate Between Types of Reports 16 - Summarizing the Importance of Data Governance Define Data Governance Understand Access Requirements and Policies Understand Security Requirements Understand Entity Relationship Requirements 17 - Applying Quality Control to Data Describe Characteristics, Rules, and Metrics of Data Quality Identify Reasons to Quality Check Data and Methods of Data Validation 18 - Explaining Master Data Management Concepts Explain the Basics of Master Data Management Describe Master Data Management Processes Additional course details: Nexus Humans CompTIA Data Plus (DA0-001) 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 CompTIA Data Plus (DA0-001) 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.

3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | Plus 10 CPD Courses | Lifetime Access