Unlock the power of Ansible in DevOps with this in-depth video course. From beginner to expert, this course covers everything you need to know about Ansible, accompanied by hands-on exercises that you can practice right in your browser. No prior experience needed.
This course is perfect for the individuals who want to deliver high-quality products, deal with rapidly changing requirements, transition into an Agile product management role, coach a product owner/product manager on Agile Scrum techniques, improve the performance of your team as a product owner/product manager, and individuals who want a professional Scrum Product Owner certification.
Ideal for beginners, the Complete Java Developer Course: From Beginner to Master is designed to get you coding in Java as quickly and confidently as possible. You will learn all the theory behind the code, while also building some exciting portfolio projects such as Mad Libs clone, tic-tac-toe, and more.
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.
The Microsoft Excel course is designed to teach you everything you need to know about Excel from scratch. This comprehensive, instructor-guided training will help you gain a thorough understanding of Excel’s essential features and functions, enabling you to kickstart your career or enhance your current skills. Whether you are just starting out or looking to build on your knowledge, this course will equip you with the most in-demand skills required in today's competitive job market.
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
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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.
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.
Learn new Android APIs such as RoomDatabase, ML Kit for face recognition, Cloud Firestore, Firebase, Maps, and the Android Studio IDE (integrated development environment)