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Whether you are a beginner or looking to sharpen your existing skills, this Software Engineering is the ideal choice. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Software Engineering Bundle is ideal for: Aspiring programmers seeking comprehensive language expertise. Web developers aiming to build responsive and engaging sites. Tech enthusiasts interested in AI, machine learning, and 3D programming. Individuals looking to enter the world of app development. Requirements You will not need any prior background or expertise in this Software Engineering bundle. 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This course covers the complete AWS Application Stacks using Cloud Development Kit. Learn to deploy simple-to-complex resources in AWS using CDK and launch several stacks and templates. This course assumes you know how to use the AWS Cloud. It will help you transform your solution architecting skills into CDK Stack.
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This Data Analysis with Data Science & Machine Learning Bundle Consists of the following Premium courses: Course 01: Introduction to Data Analysis Course 02: Data Analytics with Tableau Course 03: Complete Google Analytics Course Course 04: Python for Data Analysis Course 05: Quick Data Science Approach from Scratch Course 06: R Programming for Data Science Course 07: Learn MySQL from Scratch for Data Science and Analytics Course 08: Master JavaScript with Data Visualization Course 09: Excel Data Analysis Course 10: Statistics & Probability for Data Science & Machine Learning Course 11: Root Cause Analysis Course 12: Google Data Studio: Data Analytics Course 13: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query Course 14: Business Intelligence and Data Mining Masterclass Learning Outcomes: Develop a solid understanding of data analysis techniques. Learn how to collect, manage, and manipulate data effectively. Gain knowledge in the programming languages commonly used in data analysis, such as Python and R. Become proficient in data visualisation and presentation. Develop an understanding of machine learning algorithms and their application in data analysis. Learn how to use various data analysis software, including Tableau and Google Analytics. The Data Analysis with Data Science & Machine Learning bundle includes a variety of courses aimed at providing theoretical knowledge in the field of data analysis. The bundle covers a wide range of topics, starting with the basics of data analysis such as data cleaning, exploration, and visualisation. With courses such as Introduction to Data Analysis, Data Analytics with Tableau, Complete Google Analytics Course, Python for Data Analysis, Quick Data Science Approach from Scratch, R Programming for Data Science, Learn MySQL from Scratch for Data Science and Analytics, and Master JavaScript with Data Visualization, learners can get a comprehensive understanding of data analysis concepts. The course material is presented in a theoretical format to help learners gain a deep understanding of the topics. Learners can engage with the material at their own pace. The course content is presented in a way that is easy to understand, making it ideal for those who are new to the field of data analysis. Course Curriculum: Data Analysis with Data Science & Machine Learning Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding CPD 140 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Professionals seeking to upskill and enhance their data analysis knowledge and abilities. Individuals interested in pursuing a career in data analysis, data science or machine learning. Business owners or entrepreneurs looking to gain insights into their data and make data-driven decisions. Students or recent graduates seeking to gain valuable experience and knowledge in data analysis. Anyone looking to expand their knowledge and understanding of data analysis and its useful applications. Requirements This Data Analysis with Data Science & Machine Learning course has been designed to be fully compatible with tablets and smartphones. Career path Data Analyst: £24k-£42k per annum. Business Intelligence Analyst: £25k-£60k per annum. Data Scientist: £27k-£65k per annum. Machine Learning Engineer: £28k-£80k per annum. Business Analyst: £24k-£52k per annum. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - £10 You will get the Hard Copy certificate for the Data Analysis with Data Science & Machine Learning course absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.
Duration 5 Days 30 CPD hours This course is intended for In order to be successful in this course you should have incoming hands-on experience with another programming language. This course is not for non-developers or new developers. Possible roles that may attend this course include: Software Developers: Professionals who have been working with other programming languages and want to expand their skillset by learning Java and its object-oriented features. Web Developers: Those who work on web applications and want to enhance their back-end development capabilities with Java. Mobile App Developers: Developers who wish to enter the world of Android app development, where Java is a widely used language for creating mobile applications. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how?it relates to OO programming and the Object Model Learn to use Java exception handling Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Become familiar with the concept of functional programming using Lambda Expressions Process large amounts of data using the Stream API introduced in Java 8 Discover the new Date/Time API Use the JDBC API for database access Work with annotations Take advantage of the Java tooling that is available with the programming environment being used in the class Java 8 Features: Lambda Expressions, Method and Constructor references, The Streams API, Collectors, The Optional class Geared for experienced developers, Basic Java Programming for Developers New to OO, this hands-on, workshop-style course will provide you with an immersive learning experience that will expand your skillset and open doors to new opportunities within the ever-growing technology landscape. Mastering Java and its powerful capabilities will provide you with the competitive edge you need to stand out in today's fast-paced development world. Working in a hands-on learning environment led by our expert coach, you?ll thoroughly explore the foundations of the Java platform, essential programming concepts, and advanced topics, ensuring you acquire a strong understanding of the language and its ecosystem. The object-oriented programming principles taught in this course promote code reusability and maintainability, enabling you to streamline development processes and reduce long-term costs. As you progress through the course, you will also gain familiarity with using an IDE, enhancing your development workflow and collaboration with other Java developers, enabling you to integrate seamlessly into new projects and teams. You?ll also gain practical experience in applying the concepts and techniques learned, solidifying your newly acquired skills and facilitating their direct application in real-world scenarios. You?ll exit this course empowered to create robust, scalable, and efficient Java-based applications that drive innovation and growth for your organization The Java Platform The Java Platform Lifecycle of a Java Program Responsibilities of JVM Documentation and Code Reuse Using the JDK Explain the JDK?s file structure Use the command line compiler to compile a Java class Use the command line Java interpreter to run a Java application class The IntelliJ Paradigm Introduce the IntelliJ IDE The Basics of the IntelliJ interface IntelliJ Projects and Modules Creating and running Java applications Writing a Simple Class Write a Java class that does not explicitly extend another class Define instance variables for a Java class Create object instances Primitives vs Object References Implement a main method to create an instance of the defined class Adding Methods to the Class Write a class with accessor methods to read and write instance variables Write a constructor to initialize an instance with data Write a constructor that calls other constructors of the class to benefit from code reuse Use the this keyword to distinguish local variables from instance variables Object-Oriented Programming Real-World Objects Classes and Objects Object Behavior Methods and Messages Inheritance, Abstraction, and Polymorphism Encapsulation Inheritance Method Overriding Polymorphism Essential Java Programming Essential Java Programming Language Statements Arithmetic operators Operators to increment and decrement numbers Comparison operators Logical operators Return type of comparison and logical operators Use for loops Switch Expressions Switch Expressions and yield Using Strings and Text Blocks Create an instance of the String class Test if two strings are equal Get the length of a string Parse a string for its token components Perform a case-insensitive equality test Build up a string using StringBuffer Contrast String, StringBuffer,and StringBuilder Compact Strings Text Blocks Specializing in a Subclass Constructing a class that extends another class Implementing equals and toString Writing constructors that pass initialization data to parent constructor Using instanceof to verify type of an object reference Pattern matching for instanceof Overriding subclass methods Safely casting references to a more refined type Fields and Variables Discuss Block Scoping Rules Distinguish between instance variables and method variables within a method Explain the difference between the terms field and variable List the default values for instance variables Final and Static fields and methods Local Variable type inference Using Arrays Declaring an array reference Allocating an array Initializing the entries in an array Writing methods with a variable number of arguments Records Data Objects in Java Introduce records as carrier of immutable data Defining records Java Packages and Visibility Use the package keyword to define a class within a specific package Discuss levels of accessibility/visibility Using the import keyword to declare references to classes in a specific package Using the standard type naming conventions Visibility in the Java Modular System Correctly executing a Java application class The Java modular system Defining Modules Inheritance and Polymorphism Write a subclass with a method that overrides a method in the superclass Group objects by their common supertype Utilize polymorphism Cast a supertype reference to a valid subtype reference Use the final keyword on methods and classes to prevent overriding Interfaces and Abstract Classes Define supertype contracts using abstract classes Implement concrete classes based on abstract classes Define supertype contracts using interfaces Implement concrete classes based on interfaces Explain advantage of interfaces over abstract classes Explain advantage of abstract classes over interfaces Static, default and private methods in interfaces Sealed classes Introduce Sealed classes The sealed and permits modifiers Sealed Interfaces Exception Handling Introduction to Exception Handling Introduce the Exception architecture Defining a try/catch blocks Checked vs Unchecked exceptions Exceptions Defining your own application exceptions Automatic closure of resources Suppressed exceptions Handling multiple exceptions in one catch Helpful Nullpointers Enhanced try-with-resources Java Developer's Toolbox Developing applications Introduce the wrapper classes Explain Autoboxing and Unboxing Converting String representations of primitive numbers into their primitive types Defining Enumerations Using static imports Deprecating methods Advanced Java Programming Introduction to Generics Generics and Subtyping Bounded Wildcards Generic Methods Legacy Calls To Generics When Generics Should Be Used Lambda Expressions and Functional Interface Understanding the concept of functional programming Writing lambda expressions Understanding functional interfaces Collections Provide an overview of the Collection API Review the different collection implementations (Set, List and Queue) Explore how generics are used with collections Examine iterators for working with collections Using Collections Collection Sorting Comparators Using the Right Collection Lambda expressions in Collections Bonus Topics: Time Permitting Streams Understanding the problem with collections in Java Thinking of program solutions in a declarative way Use the Stream API to process collections of data Understand the difference between intermediate and terminal stream operations Filtering elements from a Stream Finding element(s) within a Stream Collecting the elements from a Stream into a List takeWhile and dropWhile intermediate operations Collectors Using different ways to collect the items from a Stream Grouping elements within a stream Gathering statistics about numeric property of elements in a stream
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