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What you will learn from this course? Gain comprehensive knowledge about digital electric circuits and intelligent electrical devices Understand the core competencies and principles of digital electric circuits and intelligent electrical devices Explore the various areas of digital electric circuits and intelligent electrical devices Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert electrician, electrical engineer or technicians Course Highlights Course Type: Self-paced online course Duration: 1 to 2 hours Tutor Support: Full tutor support is included Customer Support: 24/7 customer support is available Master In Digital Electric Circuits Course Master the skills you need to propel your career forward in digital electric circuits and intelligent electrical devices. This course will equip you with the essential knowledge and skillset that will make you a confident electrician, electrical engineer or technicians and take your career to the next level. This comprehensive master in digital electric course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this master in digital electric course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective digital electric circuits and intelligent electrical devices practice and equip you with the essential skills, confidence and competence to assist you in the digital electric circuits and intelligent electrical devices industry. You'll gain a solid understanding of the core competencies required to drive a successful career in digital electric circuits and intelligent electrical devices. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for electrician, electrical engineer or technicians or for people who are aspiring to specialise in digital electric circuits and intelligent electrical devices. Enrol in this master in digital electric course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive master in digital electric course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this digital electric circuits and intelligent electrical devices can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This master in digital electric course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This master in digital electric course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This master in digital electric course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Study Plex Subscription Study plex also provides a subscription option that allows you unlimited access to more than 700+ CPD courses for learning. You only need to spend £79 to take advantage of this fantastic offer, and you'll get an unlimited subscription for a full year. Additionally, you can cancel your membership from your account at any time by getting in touch with our friendly and devoted customer care team. Visit our subscriptions page for more details if you're interested. Why you should train with Study Plex? At Study Plex, you will have the chance to build social, technical and personal skills through a combination of extensive subjects tailored according to your interest. Along with receiving comprehensive knowledge and transferable skills, there are even more reasons o be involved with us, which include: Incredible Customer Support: We offer active customer service in the form of live chat, which you can access 24/7 Expert Tutor Support: You'll have access to our devoted and dedicated tutor support with all of our courses whenever you need it. Price Justified by Quality: We ensure that you will have the best experience possible for the price you are paying for the course. Money-back Guarantee: We provide a money-back guarantee if you are not satisfied with the course's quality. There is a 14-day time limit on this option (according to the terms and conditions). Instalment Facility: If your course costs more than £50, you can pay in three instalments using the instalment option. Satisfaction Guarantee: Our courses are designed to meet your demands and expectations by all means. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Introduction Introduction 00:05:00 Numbering Systems 00:28:00 Binary Arithmetic 00:19:00 Logic Gates 00:30:00 Flip-Flops 00:23:00 Counters & Shift Registers 00:12:00 Adders 00:10:00 Assessment Assessment - Master In Digital Electric Circuits 00:10:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Duration 5 Days 30 CPD hours This course is intended for This course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of C++ and object-oriented programming concepts. This course is for Non-Developers, or anyone who wants to have a basic understanding of and learn how to code C++ applications and syntax Overview Companies are constantly challenged to keep their applications, development projects, products, services (and programmers!) up to speed with the latest industry tools, skills, technologies and practices to stay ahead in the ever-shifting markets that make up today's fiercely competitive business landscape. The need for application, web and mobile developers and coders is seemingly endless as technologies regularly change and grow to meet the modern needs of demanding industries and clients. C++ and Programming Basics for Non-Programmers is a five-day, basic-level training course geared for IT candidates who have little or no prior experience in computer programming. Throughout this gentle introduction to programming and C++, students will learn to create applications and libraries using C++ using best practices and sound OO development techniques for writing object-oriented programs in C++. Special emphasis is placed on object-oriented concepts and best practices throughout the training. Fundamentals of the Program Development Cycle Computer Architecture The Notion of Algorithms Source Code vs. Machine Code Compile-Time vs. Run-Time Software Program Architecture Standalone Client/Server Distributed Web-Enabled IDE (Interactive Development Environment) Concepts Looping Constructs Counter-Controlled Repetition Sentinel-Controlled Repetition Nested Control Constructs break and continue Statements Structured Programming Best Practices Writing Methods (Functions) Static vs. Dynamic Allocation Declaring Methods Declaring Methods with Multiple Parameters Method-Call Stack Scope of Declarations Argument Promotion and Casting Designing Methods for Reusability Method Overloading Arrays Purpose of Arrays Declaring and Instantiating Arrays Passing Arrays to Methods Multidimensional Arrays Variable-Length Argument Lists Using Command-Line Arguments Using Environment Variables Deeper Into Classes and Objects Controlling Access to Class Members Referencing the Current Object Using this Overloading Constructors Default and No-Argument Constructors Composition of Classes Garbage Collection and Destructors The finalize Method Static Class Members Defining Classes Using Inheritance Application Development Fundamentals Structure of a C++ Program Memory Concepts Fundamental Data Type Declarations Fundamental I/O Concepts Fundamental Operators Arithmetic Operators Logical Operators Precedence and Associativity Building and Deploying a C++ Program Superclasses and Subclasses Advantages of Using Inheritance protected Class Members Constructors in Subclasses Increasing Convenience by Using Polymorphism Purpose of Polymorphic Behavior The Concept of a Signature Abstract Classes and Methods final Methods and Classes Purpose of Interfaces Using and Creating Interfaces Common Interfaces of the C++ API Files and Streams Concept of a Stream Class File Sequential Access Object Serialization to/from Sequential Access Files Fundamental Searching and Sorting Introduction to Searching Algorithms Linear Search Binary Search Introduction to Sorting Algorithms Selection Sort Insertion Sort Merge Sort Fundamental Data Structures Dynamic Memory Allocation Linked Lists Stacks Queues Trees Exception Handling Types of Exceptions Exception Handling Overview Introduction to Classes and Objects Classes, Objects and Methods Object Instances Declaring and Instantiating a C++ Object Declaring Methods set and get Methods Initiating Objects with Constructors Primitive Types vs. Reference Types Flow Control Conditional Constructs Exception Class Hierarchy Extending Exception Classes When to Throw or Assert Exceptions Formatted Output printf Syntax Conversion Characters Specifying Field Width and Precision Using Flags to Alter Appearance Printing Literals and Escape Sequences Formatting Output with Class Formatter Strings, Characters and Regular Expressions Fundamentals of Characters and Strings String Class String Operations StringBuilder Class Character Class StringTokenizer Class Regular Expressions Regular Expression Syntax Pattern Class Matcher Class Fundamental GUI Programming Concepts Overview of Swing Components Displaying Text and Graphics in a Window Event Handling with Nested Classes GUI Event Types and Listener Interfaces Mouse Event Handling Layout Managers Additional course details: Nexus Humans C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) 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 C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) 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.

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Overview This comprehensive course on Python Programming: Beginner To Expert will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python Programming: Beginner To Expert comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Python Programming: Beginner To Expert. It is available to all students, of all academic backgrounds. Requirements Our Python Programming: Beginner To Expert is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 18 sections • 121 lectures • 15:27:00 total length •Intro To Python Section Overview: 00:05:00 •What is Python Programming: 00:10:00 •Who is This Course For: 00:05:00 •Python Programming Marketplace: 00:06:00 •Python Job Opportunities: 00:05:00 •How To Land a Python Job Without a Degree: 00:08:00 •Python Programmer Job Roles: 00:09:00 •Python from A-Z Course Structure: 00:04:00 •Getting Familiar with Python Section Overview: 00:06:00 •Installing Python on Windows: 00:10:00 •Anaconda and Jupyter Notebooks Part 1: 00:08:00 •Anaconda and Jupyter Notebooks Part 2: 00:16:00 •Comments: 00:05:00 •Python Syntax: 00:02:00 •Line Structure: 00:03:00 •Line Structure Exercise: 00:07:00 •Joining Lines: 00:05:00 •Multiple Statements on a Single Line: 00:05:00 •Indentation: 00:08:00 •Basic Data Types Section Overview: 00:08:00 •String Overview: 00:10:00 •String Manipulation: 00:07:00 •String Indexing: 00:04:00 •String Slicing: 00:08:00 •Printing: 00:10:00 •Python Variables: 00:08:00 •Integers and Floats: 00:08:00 •Booleans: 00:05:00 •Mini Project 1 : Letter Counter: 00:20:00 •Python Operators Section Overview: 00:04:00 •Comparison Operators: 00:09:00 •Arithmetic Operators: 00:08:00 •Assignment Operators: 00:04:00 •Logical Operators: 00:13:00 •Identity Operators: 00:05:00 •Membership Operators: 00:02:00 •Bitwise Operators: 00:08:00 •Python Advanced Data Types Section Overview: 00:11:00 •Sets: 00:06:00 •List Overview: 00:05:00 •List Slicing and Indexing: 00:04:00 •Tuples: 00:02:00 •When to use each one?: 00:05:00 •Compound Data Types: 00:03:00 •Dictionaries: 00:11:00 •Control Flow Part 1 Section Overview: 00:15:00 •Intro to Control Flow: 00:01:00 •Basic Conditional Statements: 00:14:00 •More Conditional Statements: 00:05:00 •For Loops: 00:10:00 •While Loops: 00:12:00 •Control Flow Part 2 Section Overview: 00:02:00 •Break Statements: 00:08:00 •Continue Statements: 00:05:00 •Zip Function: 00:07:00 •Enumerate Function: 00:04:00 •List Comprehension: 00:04:00 •Python Functions Section Overview: 00:03:00 •Intro to Functions: 00:02:00 •Python help Function: 00:03:00 •Defining Functions: 00:09:00 •Variable Scope: 00:08:00 •Doc Strings: 00:04:00 •User Input and Error Handling Section Overview: 00:02:00 •Introduction to error handling: 00:03:00 •User Input: 00:04:00 •Syntax Errors: 00:04:00 •Exceptions: 00:11:00 •Handling Exceptions Part 1: 00:08:00 •Handling Exceptions Part 2: 00:08:00 •Python Advanced Functions Section Overview: 00:05:00 •Lambda Functions: 00:05:00 •Functions args and kwargs: 00:10:00 •Iterators: 00:08:00 •Generators and Yield: 00:12:00 •Map Function: 00:14:00 •Filter Function: 00:08:00 •Python Scripting and Libraries Section Overview: 00:05:00 •What is a script: 00:01:00 •What is an IDE: 00:17:00 •What is a text editor?: 00:12:00 •From Jupyter Notebook to VScode Part 1: 00:15:00 •From Jupyter Notebook to VScode Part 2: 00:05:00 •Importing Scripts: 00:03:00 •Standard Libraries: 00:04:00 •Third Party Libraries: 00:06:00 •NumPy Section Overview: 00:04:00 •Intro to NumPy: 00:04:00 •Why use NumPy?: 00:04:00 •NumPy Arrays: 00:10:00 •Reshaping, Accessing, and Modifying: 00:07:00 •Slicing and Copying: 00:06:00 •Inserting, Appending, and Deleting: 00:10:00 •Array Logical Indexing: 00:04:00 •Broadcasting: 00:08:00 •Intro to Pandas: 00:17:00 •Pandas Series: 00:17:00 •Pandas Series Manipulation: 00:17:00 •Pandas DataFrame: 00:17:00 •Pandas DataFrame Manipulation: 00:13:00 •Dealing with Missing Values: 00:10:00 •Functional vs OOP: 00:06:00 •OOP Key Definitions: 00:04:00 •Create your First Class: 00:12:00 •How to Create and Use Objects: 00:06:00 •How to Modify Attributes: 00:12:00 •Python Decorators: 00:27:00 •Property Decorator: 00:09:00 •Class Method Decorator: 00:07:00 •Static Methods: 00:10:00 •Inheritance from A to Z: 00:21:00 •Python Career Section Overview: 00:06:00 •Getting Started with Freelancing: 00:09:00 •Building A Brand: 00:12:00 •Personal Branding: 00:13:00 •Importance of Having Website/Blog: 00:04:00 •Do's And Don'ts Of Networking: 00:06:00 •Top Freelance Websites: 00:08:00 •Creating A Python Developer Resume: 00:06:00 •Resources - Python Programming: Beginner To Expert: 00:00:00 •Assignment - Python Programming: Beginner To Expert: 00:00:00

Course Overview Julia is one of the highest performing programming languages. The Tutorials - The Julia Programming Language course is designed to train you in this valuable programing language. In this course, you will get equipped with the skills to code in Julia and add available skill sets to your resume. The Tutorials - The Julia Programming Language course will introduce you to the basic principles of Julia programming language. In this course, you will learn the steps to install Julia. You will get introduced to Julia variables, integers, sign function and more. The course will provide you with lectures based on Cher types and strings. You will start to understand all the functions of this programming language. The course will give you an extensive understanding of Julia Dict and type. By the end of the course, you will pick up all the valuable information and skills to use this language. Learn the ins and outs of Julia programming language from the Tutorials - The Julia Programming Language course. This course will increase your abilities and boost your employability in the relevant industry. Learning Outcomes Understand the process of installing Julia Familiarize yourself with Julia variables and functions Enrich your understanding of Cher types and strings Learn the details of conditional and non-conditional blocks Grasp the skills essential for Juila Dict operations Who is this course for? This Tutorials - The Julia Programming Language course is suitable for programmers, data scientists, or individuals who want to learn a new programming language. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path The Tutorials - The Julia Programming Language course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Programmer Data Scientist Introduction Learning Julia 00:01:00 Installing Julia 00:06:00 Installing Juno 00:04:00 Begin Dancing with Julia Julia Variables 00:05:00 Julia Integers and Floats 00:05:00 Julia Convert and Comparisons 00:03:00 Rounding Operations 00:05:00 Division Function 00:04:00 Sign Function and Power 00:05:00 Complex and Rational Numbers 00:05:00 Julia Chars and Strings Julia Char type 00:03:00 String Literals 00:02:00 Extract Char and String 00:02:00 Concatenate and Interpolate 00:03:00 isEqual and Comparisons 00:04:00 Find and OccursIn 00:05:00 Repeat and Regex 00:04:00 Julia Functions Julia Function Object 00:04:00 Function Return Type 00:06:00 Functions as Objects and Arguments 00:04:00 Operators as Functions 00:02:00 Anonymous Function 00:04:00 Function Arguments Tuples 00:05:00 Unpacking Tuples 00:02:00 Varargs 00:03:00 Optional Arguments 00:03:00 Keyword Arguments 00:03:00 Conditional and Non-Conditional Blocks Do Block 00:04:00 Compound Expression 00:02:00 If Statements 00:05:00 If Statement Return Value 00:02:00 Short Circuit Evaluation 00:03:00 Loops and Exceptions For Loop 00:02:00 Control and Nest For Loops 00:03:00 Exceptions 00:03:00 Julia Try and Catch 00:03:00 While Loop 00:02:00 Variable Scope 00:05:00 Arrays in Julia Arrays 00:04:00 Pop and Push 00:03:00 Multidimensional Arrays 00:03:00 Copying Arrays 00:02:00 Julia Dicts Dicts 00:02:00 Dict Operations 00:02:00 More Dict Operations 00:04:00 More Cool Dict Operations 00:03:00 One More Cool Dict Operation 00:04:00 Broadcasting 00:04:00 Julia Types Julia Types 00:01:00 Verify and Specify Types 00:03:00 More Verification and Specification 00:05:00 Julia Methods 00:02:00 Composite Types 00:05:00 Mutable Structs 00:02:00 Constructor Functions 00:04:00 Modules and Packages Julia Modules 00:02:00 Using Packages 00:04:00 User Defined Modules 00:05:00 Working with Text Files Reading Text Files 00:04:00 Writing To Text Files 00:03:00 Writing Collections To Files 00:02:00 Julia Date and Time Date And Time 00:03:00 Date Queries 00:02:00 Date Arithmetic 00:03:00 Meta Programming in Julia Meta Programming 00:02:00 Quoted Expression 00:04:00 Macros 00:02:00 REST APIs and MySQL Using Genie 00:04:00 Payloads and POST Requests 00:05:00 Julia and MySQL 00:08:00 DataFrames and Plots DataFrames 00:05:00 Plotting with Plots 00:02:00 Where to go from here 00:01:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

Embark on a journey into the world of Android app development with our comprehensive Kotlin Programming: Android Coding Bible course. This in-depth training will equip you with the knowledge and skills to master Kotlin, a modern and powerful programming language specifically designed for Android development. Whether you're a complete beginner or an experienced programmer seeking to expand your skillset, this course will guide you through the fundamentals of Kotlin, covering topics such as syntax, data types, variables, operators, control flow statements, functions, error handling, and null safety. You'll gain a solid understanding of object-oriented programming principles and learn how to effectively utilize collections to manage and process data. Learning Outcomes Master the fundamentals of Kotlin programming language for Android development Gain a thorough understanding of syntax, data types, variables, operators, and control flow statements Learn how to create and utilize functions to structure and modularize code Effectively handle errors and exceptions to ensure robust and reliable applications Implement null safety mechanisms to prevent NullPointerExceptions and enhance code stability. Why choose this Kotlin Programming: Android Coding Bible course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Kotlin Programming: Android Coding Bible course for? Aspiring Android developers seeking to master Kotlin programming language Individuals with prior programming experience looking to transition to Android development Software engineers aiming to expand their skillset with Kotlin and Android development expertise Students of computer science or related fields interested in learning Android app development Enthusiasts passionate about creating mobile applications for the Android platform. Career path Android Developer (£35,000 - £55,000) Senior Android Developer (£45,000 - £65,000) Android App Architect (£55,000 - £75,000) Mobile Application Developer (£30,000 - £50,000) Software Engineer (£40,000 - £60,000) Full-Stack Developer (£45,000 - £65,000) Prerequisites This Kotlin Programming: Android Coding Bible does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Kotlin Programming: Android Coding Bible was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction & Setup Introduction To This Course 00:02:00 Windows Setup 00:13:00 Mac Setup 00:10:00 Linux Setup 00:12:00 Online Code Editor 00:02:00 Section 02: Basics Variables 00:06:00 Data Types 00:06:00 String 00:05:00 Array 00:07:00 Data Type Conversion 00:05:00 Comments 00:04:00 Arithmetic Operators 00:07:00 Relational Operators 00:06:00 Assignment Operators 00:06:00 Unary Operators 00:05:00 Bitwise Operators 00:09:00 Logical Operators 00:04:00 Input & Output 00:03:00 Section 03: Control Statements Conditional if Statement 00:05:00 When Statement 00:07:00 For Loop 00:04:00 While Loop 00:04:00 do while Loop 00:04:00 Break Statement 00:04:00 Continue Statement 00:04:00 Section 04: Functions Basic Functions 00:03:00 Function Parameters 00:04:00 Return Values 00:04:00 Recursion 00:04:00 Default & Named Arguments 00:06:00 Lambda Function 00:04:00 Higher Order Function 00:05:00 Inline Function 00:02:00 Section 05: Error/Exception Handling Try Catch Block 00:04:00 Try Catch Expression 00:05:00 Multiple Catch Block 00:05:00 Nested Try Catch Block 00:05:00 Finally Block 00:02:00 Throw Keyword 00:02:00 Section 06: NULL Safety Nullable & Non Nullable Types 00:03:00 Smart Cast 00:02:00 Unsafe and Safe Cast 00:03:00 Elvis Operator 00:04:00 Section 07: Collections List: listOf Function 00:06:00 List: mutableListOf Function 00:05:00 List: arrayListOf Function 00:06:00 Map: mapOf Function 00:07:00 Map: HashMap 00:08:00 Map: hashMapOf Function 00:05:00 Map: mutableMapOf Function 00:04:00 Set: setOf Function 00:04:00 Set: mutableSetOf Function 00:04:00 Set: HashSet 00:04:00 Section 08: Classes & Objects Basic Example 00:07:00 Nested and Inner Class 00:06:00 Constructors 00:05:00 Visibility Modifiers 00:06:00 Inheritance 00:05:00 Method Overriding 00:04:00 Property Overriding 00:02:00 Abstract Class 00:03:00 Superclass 00:03:00 Data Class 00:05:00 Multiple Class Inheritance & Interfaces 00:03:00 Sealed Class 00:03:00 Extension Function 00:03:00 Generics 00:05:00 Section 09: Extras Integer Type Range 00:05:00 Regex 00:04:00 Call Java from Kotlin 00:03:00 Call Kotlin from Java 00:02:00 Section 10: Resource Resource 00:00:00 Assignment Assignment - Kotlin Masterclass Programming Course: Android Coding Bible 00:00:00

Duration 3 Days 18 CPD hours This course is intended for This is an introductory level SQL course, appropriate for anyone needing to interface with an Oracle database or those needing a general understanding of Oracle database functionality. That would include end users, business analysts, application developers and database administrators. Overview Working in a hands on learning environment led by our expert practitioner, attendees will explore: Basic RDBMS Principles The SQL Language and Tools Using SQL Developer SQL Query Basics WHERE and ORDER BY Functions ANSI 92 Joins ANSI 99 Joins Subqueries Regular Expressions Analytics A company?s success hinges on responsible, accurate database management. Organizations rely on highly available data to complete all sorts of tasks, from creating marketing reports and invoicing customers to setting financial goals. Data professionals like analysts, developers and architects are tasked with creating, optimizing, managing and analyzing data from databases ? with little room for error. When databases aren?t built or maintained correctly, it?s easy to mishandle or lose valuable data. Our SQL Programming and Database Training Series provides students with the skills they require to develop, analyze and maintain data and in correctly structured, modern and secure databases. A full presentation of the basics of relational databases and their use are also covered. Basic RDBMS Principles Relational design principles Accessing data through a structured query language Entity relationship diagrams Data Domains Null values Indexes Views Denormalization Data Model Review The SQL Language and Tools Using SQL*Plus Why Use SQL*Plus When Other Tools Are Available? Starting SQL*Plus EZConnect SQL Commands PL/SQL Commands SQL*Plus Commands The COLUMN Command The HEADING Clause The FORMAT Clause The NOPRINT Clause The NULL Clause The CLEAR Clause Predefined define variables LOGIN.SQL Command history Copy and paste in SQL*Plus Entering SQL commands Entering PL/SQL commands Entering SQL*Plus commands Default output from SQL*Plus Entering Queries What about PL/SQL? Using SQL Developer Choosing a SQL Developer version Configuring connections Creating A Basic Connection Creating A TNS Connection Connecting Configuring preferences Using SQL Developer The Columns Tab The Data Tab The Constraints Tab The Grants Tab The Statistics Tab Other Tabs Queries In SQL Developer Query Builder Accessing Objects Owned By Other Users The Actions Pulldown Menu Differences between SQL Developer and SQL*Plus Reporting Commands Missing In SQL Developer General Commands Missing In SQL Developer Data Dictionary report User Defined reports Using scripts in SQL Developer WHERE and ORDER BY WHERE clause basics Comparison operators Literals and Constants in SQL Simple pattern matching Logical operations The DUAL table Arithmetic operations Expressions in SQL Character operators Pseudo columns Order by clause basics Ordering Nulls Accent and case sensitive sorts Sampling data WHERE and ORDER BY in SQL Developer All, Any, Some Functions The basics of Oracle functions Number functions Character functions Date functions Conversion functions Other functions Large object functions Error functions The RR format mode; Leveraging your knowledge ANSI 92 JOINS Basics of ANSI 92 Joins Using Query Builder with multiple tables Table Aliases Outer joins Outer Joins In Query Builder Set operators Self-referential joins Non-Equijoins ANSI 99 Joins Changes with ANSI99 CROSS Join NATURAL Join JOIN USING JOIN ON LEFT / RIGHT OUTER JOIN FULL OUTER JOIN Subqueries Why use subqueries? WHERE clause subqueries FROM clause subqueries HAVING clause subqueries CORRELATED subqueries SCALAR subqueries DML and subqueries EXISTS subqueries Hierarchical queries TOP N AND BOTTOM N queries Creating subqueries using Query Builder Regular Expressions Available Regular Expressions Regular Expression Operators Character Classes Pattern matching options REGEX_LIKE REGEXP_SUBSTR REGEXP_INSTR REGEXP_REPLACE REGEXP_COUNT Analytics The WITH clause Reporting aggregate functions Analytical functions User-Defined bucket histograms The MODEL clause PIVOT and UNPIVOT Temporal validity More Analytics RANKING functions RANK DENSE_RANK CUME_DIST PERCENT_RANK ROW_NUMBER Windowing aggregate functions RATIO_TO_REPORT LAG / LEAD Linear Regression functions Inverse Percentile functions Hypothetical ranking functions Pattern Matching Additional course details: Nexus Humans Introduction to SQL Programming Basics (TTSQL002) 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 Introduction to SQL Programming Basics (TTSQL002) 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.

Are you drained when taking care of kids? Are you having difficulties in keeping up with their energy? If yes, then it's time for you to find other ways to keep them entertained and this Diploma in Children Entertainment is perfect for your needs Description: You'll discover that this diploma course for on point and full of significant learning, thoughts, techniques, strategies, and instruments as we've designed this course and book in view of one objective: set you on your way to a flourishing, satisfying vocation in children's entertainment. Children's entertainment is not an occupation. Children's entertainment is a calling, an occupation, much like what constrains a cleric to pick an existence devoted to the care of his group. In this course you will learn the necessary skills, knowledge and information of children entertainment.  Who is the course for? Professionals who are into the Children's Entertainment and people who want to improve their Children Entertainment. People who have an interest in Children's Entertainment What will I learn? Making a Living from Children's Entertainment Being a Part-time or Full-time in Children's Entertainment Where to Start How to Understand the Psychology of Little Kids How to Handle Groups of Children Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment:  At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognised accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of applying for NUS Extra Discount Card; 24/7 student support via email. Career Path: The Diploma in Children's Entertainment is a useful qualification to possess, and would be beneficial for the following careers: Child and Family Social Worker Early Childhood Educator Preschool, Kindergarten, and Elementary Teachers Pediatric Nutritionist or Dieticians Private Nanny. Course Curriculum Diploma in Children Entertainment Introduction 00:15:00 HOUSEHOLD GAMES AND AMUSEMENTS 01:30:00 CHURCH AND SCHOOL SOCIALS 01:30:00 OPTICAL ILLUSIONS 01:30:00 TABLE GAMES FOR ADULTS 01:30:00 OUTDOOR GAMES FOR ADULTS 01:00:00 HOLIDAY GAMES AND AMUSEMENTS 01:00:00 OUTDOOR GAMES FOR GIRLS 01:00:00 PASTIMES FOR CHILDREN 00:15:00 INDOOR GAMES FOR YOUNG CHILDREN 01:00:00 OUTDOOR GAMES FOR YOUNG CHILDREN 01:00:00 SINGING GAMES FOR CHILDREN 01:00:00 GAMES OF ARITHMETIC 01:00:00 ONE HUNDRED CONUNDRUMS 01:00:00 Mock Exam Mock Exam- Diploma in Children Entertainment 00:20:00 Final Exam Final Exam- Diploma in Children Entertainment 00:20:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Register on the Kotlin Masterclass Programming Course: Android Coding Bible today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Kotlin Masterclass Programming Course: Android Coding Bible is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Kotlin Masterclass Programming Course: Android Coding Bible Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Kotlin Masterclass Programming Course: Android Coding Bible, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.  Course Content Section 01: Introduction & Setup Introduction To This Course 00:02:00 Windows Setup 00:13:00 Mac Setup 00:11:00 Linux Setup 00:12:00 Online Code Editor 00:02:00 Section 02: Basics Variables 00:06:00 Data Types 00:06:00 String 00:05:00 Array 00:07:00 Data Type Conversion 00:05:00 Comments 00:04:00 Arithmetic Operators 00:07:00 Relational Operators 00:06:00 Assignment Operators 00:06:00 Unary Operators 00:05:00 Bitwise Operators 00:09:00 Logical Operators 00:04:00 Input & Output 00:03:00 Section 03: Control Statements Conditional if Statement 00:05:00 when Statement 00:07:00 For Loop 00:04:00 while Loop 00:04:00 do while Loop 00:04:00 Break Statement 00:04:00 Continue Statement 00:04:00 Section 04: Functions Basic Functions 00:03:00 Function Parameters 00:04:00 Return Values 00:04:00 Recursion 00:04:00 Default & Named Arguments 00:06:00 Lambda Function 00:04:00 Higher Order Function 00:05:00 Inline Function 00:02:00 Section 05: Error/Exception Handling Try Catch Block 00:04:00 Try Catch Expression 00:05:00 Multiple Catch Block77 00:05:00 Nested Try Catch Block 00:05:00 Finally Block 00:02:00 Throw Keyword 00:02:00 Section 06: NULL Safety Nullable & Non Nullable Types 00:03:00 Smart Cast 00:02:00 Unsafe and Safe Cast 00:03:00 Elvis Operator 00:04:00 Section 07: Collections List: listOf Function 00:06:00 List: mutableListOf Function 00:05:00 List: arrayListOf Function 00:06:00 Map: mapOf Function 00:07:00 Map: HashMap 00:08:00 Map: hashMapOf Function 00:05:00 Map: mutableMapOf Function 00:04:00 Set: setOf Function 00:04:00 Set: mutableSetOf Function 00:04:00 Set: HashSet 00:04:00 Section 08: Classes & Objects Basic Example 00:07:00 Nested and Inner Class 00:06:00 Constructors 00:05:00 Visibility Modifiers 00:06:00 Inheritance 00:05:00 Method Overriding 00:04:00 Property Overriding 00:02:00 Abstract Class 00:03:00 Superclass 00:03:00 Data Class 00:05:00 Multiple Class Inheritance & Interfaces 00:03:00 Sealed Class 00:03:00 Extension Function 00:03:00 Generics 00:05:00 Section 09: Extras Integer Type Range 00:05:00 Regex 00:04:00 Call Java from Kotlin 00:03:00 Call Kotlin from Java 00:02:00 Section 10: Resource Resource 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.