Learn how to build a RESTful API using ASP.NET Core 6, and then consume it in a modern Blazor single-page application. Along the way, you will review clean coding principles and patterns, RESTful standards, logging tools, database development and management, and application testing and deployment strategies.
Go hands-on and create a fully functional, low-maintenance, modern responsive website using HTML5, CSS3, and JavaScript. No WordPress, no Bootstrap, no jQuery no libraries of any kind. Learn to share header, nav, and footer HTML code across web pages using PHP, which most web hosting providers include for free. You'll learn to choose fonts, a color scheme, create a header, nav bar, and footer, make the site responsive so it looks and works as well on phones and mobile devices as it does on larger screens. Use free FontAwesome fonts to add social media icons and stylized lists to your site. Create your own media cards, and learn some tricks for modernizing your HTML form controls. What Will I Learn? Create a modern responsive website using just HTML5, CSS3, and JavaScript - and perhaps a few lines of PHP code if you're like to share header, nav, and footer content across pages. Requirements Some hands-on experience with basic HTML and CSS and a code editor. Basic file and folder skills for Mac or Windows. Who is the target audience? People learning web development who want to focus on the core front-end languages HTML5, CSS3, and JavaScript WITHOUT Bootstrap, jQuery, or other libraries. Beginning developers looking to create great, low-maintenance websites for themselves or others. Developers who are looking for easy ways to share content, like header, nav, and footer HTML code, across pages. Get Started What This is About 00:05:00 Start Building 00:18:00 Choose Your Fonts 00:05:00 Choose Your Color Scheme 00:05:00 Create the Nav Bar 00:11:00 Add a Page Footer 00:08:00 Beyond the Basic Structure Style the Body Content 00:05:00 Make it Responsive 00:10:00 Activate the Hamburger Menu 00:17:00 Make it Professional with Animations 00:04:00 Share Content Across Pages Why Share Content Across Pages? 00:08:00 Install AMPPS - Windows 00:11:00 Install AMPPS - Mac 00:13:00 Break Out the Shared Content 00:10:00 Professional-Grade Touches External JavaScript and Meta Tags 00:07:00 Adding More Pages to the Site 00:06:00 Highlight the Current Page in the Nav Bar 00:14:00 More Body Text Styling 00:10:00 Creating the Media Cards 00:13:00 Styling Lists 00:09:00 Styling Form Controls 00:15:00
In this course, you will start as a beginner without any previous knowledge about hacking. The course focuses on both practical and theoretical sides to ensure that you understand the attack before performing it. Learn how black hat hackers hack and White hat hackers secure Windows OS with the help of advanced methods.
Course Overview Find the ultimate guide for learning Django framework by taking this Django REST Framework - Full Stack Python APIs using Python course. In this course, you will learn the techniques to build Python Rest APIs using the Django framework. This Django REST Framework - Full Stack Python APIs using Python course breaks tools and techniques to enhance your understanding of the Django framework and its features. The project-based course provides step-by-step instructions on how to create a Rest API from scratch. You will start the course by learning how to set up a Django development environment and proceed towards the fundamental steps in creating a Rest API project. You will gain the knowledge to develop Rest APIs using function-based views and class-based views. You will also learn the best practices to secure your Rest APIs. Learning Outcomes Gain in-depth knowledge Rest API Learn hope to configure the Rest API Identify the importance of Django Framework Deepen your understanding of mixins and generic views Know how to create Rest APIs using function based views Learn how to create viewset Be able to create Rest APIs with class based views Who Is This Course For? The Django REST Framework - Full Stack Python APIs using Python course is incredibly beneficial for professionals interested in learning how to create Python Rest APIs in Django Framework. Entry Requirement This course is available to all learners of all academic backgrounds. Learners should be aged 16 or over. Good understanding of English language, numeracy and ICT skills are required to take this course. Certification After you have successfully completed the course, you will obtain an Accredited Certificate of Achievement. And, you will also receive a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy for £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 and materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; United Kingdom & internationally recognized accredited qualification; Access to course content on mobile, tablet and desktop from anywhere, anytime; Substantial career advancement opportunities; 24/7 student support via email. Career Path Django REST Framework - Full Stack Python APIs using Python provides essential skills that will make you more effective in your role. It would be beneficial for any related profession in the industry, such as Full Stack- Lead Software Developer Python/Django Developer Backend Developer Software Engineer-Python Unit 01: Start Here Module 01: Course and Instructor Introduction 00:03:00 Module 02: How to make the best of this course 00:02:00 Unit 02: Introduction Module 01: What is REST? 00:06:00 Module 02: Why REST 00:08:00 Module 03: What and Why DJango REST Framework 00:06:00 Unit 03: Software Setup Module 01: Install DJango 00:03:00 Module 02: Install DJango REST Framework 00:01:00 Module 03: Install MySql and MySql workbench 00:03:00 Module 04: Launch MySql workbench 00:02:00 Module 05: Install python mysqlclient 00:01:00 Module 06: Install ATOM 00:03:00 Module 07: Install Postman 00:01:00 Unit 04: REST in Action Module 01: Create the Project 00:03:00 Module 02: Create a view 00:02:00 Module 03: Configure the URL and TEST 00:03:00 Module 04: Create app level urls 00:02:00 Module 05: Create a model class 00:03:00 Module 06: Configure the database and run migrations 00:03:00 Module 07: Use the model in the view and test 00:03:00 Unit 05: Function Based Views and Serializers Module 01: DRF Components 00:06:00 Module 02: Function Based Views 00:05:00 Module 03: Serializers 00:04:00 Module 04: Create the Project 00:02:00 Module 05: Create the Model 00:02:00 Module 06: Create the Serializer 00:02:00 Module 07: GET single student 00:04:00 Module 08: Create Student 00:04:00 Module 09: Implement Non Primary Key Based Operations 00:07:00 Module 10: Use @api_view 00:01:00 Module 11: Configure the URLs 00:02:00 Module 12: Test 00:07:00 Module 13: Test Using Postman 00:04:00 Unit 06: Class Based Views Module 01: Introduction 00:03:00 Module 02: Create the Project 00:03:00 Module 03: Implement Non Primary Key Based Operations 00:06:00 Module 04: Implement Primary Key Based Operations 00:07:00 Module 05: Configure the URLs and TEST 00:04:00 Unit 07: Mixins Module 01: Introduction 00:05:00 Module 02: Non Primary Key based operations 00:04:00 Module 03: Primary Key based operations 00:02:00 Module 04: Configure the URLs and TEST 00:02:00 Unit 08: Generic Views Module 01: Generics 00:03:00 Module 02: Generics in action 00:03:00 Unit 09: ViewSets Module 01: Introduction 00:03:00 Module 02: Create ViewSet 00:02:00 Module 03: Configure URLs and Test 00:04:00 Unit 10: Nested Serializers Module 01: Create the project 00:02:00 Module 02: Create model 00:03:00 Module 03: Create Serializers 00:04:00 Module 04: Create REST endpoints 00:03:00 Module 05: Configure URLs 00:02:00 Module 06: Test 00:03:00 Unit 11: Pagination Module 01: Introduction 00:06:00 Module 02: Pagination in action 00:05:00 Module 03: Pagination at class level 00:03:00 Module 04: Using LimitOffsetPagination 00:01:00 Unit 12: Security Module 01: Introduction 00:04:00 Module 02: Authentication in action 00:03:00 Module 03: Authorization in action 00:06:00 Module 04: Global Security 00:04:00 Unit 13: Flight Reservation API Module 01: Usecase 00:01:00 Module 02: Create the Project 00:01:00 Module 03: Create Model Classes 00:03:00 Module 04: Create Reservation Model 00:01:00 Module 05: Create Serializers 00:01:00 Module 06: Create ViewSets 00:02:00 Module 07: Configure the Router 00:02:00 Module 08: Run Migrations 00:01:00 Module 09: Initial round of testing 00:04:00 Module 10: Implement findFlights endpoint 00:03:00 Module 11: Test findFlights 00:05:00 Module 12: Implement Save Reservation 00:06:00 Module 13: Test Save Reservation 00:04:00 Unit 14: Validations Module 01: In-Built Validations 00:04:00 Module 02: Allowing Blank and Null Values 00:02:00 Module 03: Create Custom Validator 00:05:00 Module 04: Two more ways 00:07:00 Unit 15: Token Auth Module 01: Introduction 00:03:00 Module 02: Configure Token Auth 00:05:00 Module 03: Create Users and Token 00:04:00 Module 04: Token Auth in action 00:03:00 Module 05: Automate Token Creation 00:09:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00
Introduction Ever found yourself swamped with academic reports and no time to complete them? You're not alone. Academic report writing is a crucial part of your education, but it can be overwhelming. That's where report writing services come in. These services can be a lifesaver, helping you manage your workload and ensure top-notch quality. Let's dive into the world of report writing services and see how they can meet your academic needs. Understanding Academic Reports Definition and Purpose Academic reports are structured documents that present information clearly and concisely. They're used to communicate research findings, analyze issues, or explore topics in-depth. Unlike essays, reports often include sections like methodologies, findings, and recommendations. Different Types of Academic Reports From lab reports and research papers to case studies and book reports, academic reports come in various forms. 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Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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.
Learn new Android APIs such as RoomDatabase, ML Kit for face recognition, Cloud Firestore, Firebase, Maps, and the Android Studio IDE (integrated development environment)
This complete training program comprising levels 1 and 2 is divided into multi-sequential sections to let you gain comprehensive knowledge and understanding of SQL and data analysis. This two-level course is designed to kickstart your SQL knowledge and perform various data analysis tasks and implement SQL in projects independently and efficiently.
Welcome to 'Python Programming for Non Programmers Level 5,' a course specially designed for those new to the world of coding. This program starts with a comprehensive introduction to Python, a versatile programming language favored in numerous fields. Progressing to the second unit, participants will familiarize themselves with the initial steps of Python programming, setting a strong foundation for future learning. The course then advances to conditional branching in Python, an essential skill for logical problem-solving in coding. A highlight of this course is the practical project: building the game 'Rock Paper Scissors'. This engaging task not only consolidates learning but also adds a fun element to the process. The curriculum further includes critical topics like string operations, date and time functionalities, and the nuances of file handling in Python. Learners will navigate through the complexities of Python data structures-tuples, lists, and dictionaries-and learn to craft user functions, enhancing their coding capabilities. The course also covers email automation, ingenious import tactics, interfacing with operating systems, and handling exceptions with finesse. Furthermore, learners will get hands-on experience with package installation, scheduling tasks in Python, and managing databases using SQLite. The course wraps up with insights on running Python programs via command prompt and Jupyter Notebook, ensuring learners are well-equipped for real-world applications. Learning Outcomes Acquire foundational knowledge and setup skills in Python programming. Master conditional branching for effective problem-solving in code. Complete a practical coding project to solidify Python skills. Learn essential Python operations, including string handling and file management. Explore and apply advanced Python concepts for real-world applications. Why choose this Python Programming for Non Programmers Level 5 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 Python Programming for Non Programmers Level 5 course for? Beginners eager to learn Python from scratch. Non-technical professionals desiring to add coding skills to their portfolio. Educators keen to integrate Python into their teaching methodologies. Businesspersons interested in understanding coding fundamentals for tech-based solutions. Enthusiasts exploring programming as a new hobby or career path. Career path Entry-Level Python Programmer: £25,000 - £40,000 Python-Enabled Data Analyst: £28,000 - £45,000 Python Automation Engineer: £30,000 - £50,000 Technical Support Analyst with Python Skills: £22,000 - £35,000 Python Web Developer: £26,000 - £42,000 Quality Assurance Analyst with Python Expertise: £24,000 - £38,000 Prerequisites This Python Programming for Non Programmers Level 5 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Programming for Non Programmers Level 5 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 Unit 01: Introduction to Python Programming Section 01: Course Introduction 00:02:00 Unit 02: Getting Started with Python Section 01: Software Installation 00:02:00 Section 02: Hello World Program 00:06:00 Section 03: Input and Output 00:07:00 Section 04: Calculating Average of 5 Numbers 00:03:00 Unit 03: Conditional Branching with Python Section 01: If Loop In Python 00:06:00 Section 02: Program Using If Else part 1 00:03:00 Section 03: Program Using If Else part 2 00:08:00 Section 04: Program for Calculator 00:02:00 Section 05: Program Using For Loop 00:08:00 Section 06: For Table 00:05:00 Section 07: For loop and Mathematical Operator in Python 00:04:00 Section 08: Factorial of Number Using Python 00:06:00 Section 09: Program Using While 00:05:00 Section 10: While Loop Example 00:07:00 Section 11: Tasks for Practice 00:02:00 Unit 04: Importing external/internal library in python Section 01: Importing Library in Python 00:07:00 Unit 05: Project Rock Paper and Scissors Section 01: Rock Paper and Scissor Game 00:06:00 Unit 06: Strings Operation in Python Section 01: Program Using String part 1 00:05:00 Section 02: Program using String 2 00:06:00 Section 03: Program Using String 3 00:06:00 Section 04: Program Using String part 4 00:03:00 Unit 07: Date and time in Python Section 01: Use of Date and Time part 1 00:05:00 Section 02: Use of Date and Time part 2 00:05:00 Unit 08: File Handling, read and write using Python Section 01: File Handling Part 1 00:08:00 Section 02: File Handling Part 2 00:07:00 Unit 09: Data Storage Structures, Tuple, List and Dictionary Section 01: Tuple in Python Part 1 00:10:00 Section 02: Tuple in Python Part 2 00:07:00 Section 03: Using Lists part 1 00:07:00 Section 04: Using List part 2 00:12:00 Section 05: Using Lists part 3 00:06:00 Section 06: Using Lists part 4 00:08:00 Section 07: Using Lists part 5 00:02:00 Section 08: Use of Dictionary Part 1 00:04:00 Section 09: Use of Dictionary Part 2 00:05:00 Section 10: Use of Dictionary Part 3 00:08:00 Section 11: Use of Dictionary Part 4 00:07:00 Unit 10: Writing user functions in Python Section 01: Function in Python Part 1 00:06:00 Section 02: Function in Python Part 2 00:05:00 Section 03: Function in Python Part 3 00:04:00 Section 04: Function in Python Part 4 00:07:00 Section 05: Function in Python Part 5 00:08:00 Unit 11: Sending mail Section 01: Send Email 00:09:00 Unit 12: Import Tricks in Python Section 01: Import Study part 1 00:07:00 Section 02: Import Study part 2 00:03:00 Unit 13: Import Operating System and Platform Section 01: Importing OS 00:06:00 Section 02: Import Platform 00:05:00 Unit 14: Exceptions handling in python Section 01: Exception in Python part 1 00:11:00 Section 02: Exception in Python part 2 00:07:00 Section 03: Exception in Python part 3 00:05:00 Unit 15: Installing Packages and Scheduling In Python Section 01: Installing Packages using built in package manager 00:08:00 Section 02: Scheduler in Python 00:05:00 Unit 16: Data Base In Python using sqlite Section 01: Data Base 1 00:08:00 Section 02: Data Base 2 00:09:00 Section 03: Data Base 3 00:08:00 Section 04: Data base 4 00:07:00 Section 05: Data Base 5 00:06:00 Unit 17: Running Program from Command Prompt and jupyter Notebook Section 01: IDE_1 00:05:00 Section 02: IDE_2 00:07:00 Unit 18: Conclusion Section 01: Conclusion 00:02:00 Resources Resources - Diploma in Python Programming 00:00:00 Assignment Assignment - Diploma in Python Programming 00:00:00 Recommended Materials Workbook - Diploma in Python Programming 00:00:00
This course is about developing core skills that will stay with you for a lifetime. It is designed such that you can watch the material and follow along step-by-step. It focuses on the implementation of YOLOv4 to get you up and running. You'll be an object detecting ninja in no time and be able to graduate to more advanced content.