317 Algorithms courses delivered Online

Master the skills you need to propel your career forward in instructional design. Equip yourself with the essential knowledge and skillset that make you a confident teacher or teaching assistant and take your career to the next level. This comprehensive course is designed to help you reach your professional goals. The skills and knowledge that you will gain through studying this instructional design diploma 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 instructional design practice and equip you with the essential skills, confidence and competence to assist you in the instructional design industry. You'll gain a solid understanding of the core competencies required to drive a successful career in instructional design. Learn from expert tutors with industry experience, teaching you the latest expertise and best practice. This extensive course is designed for instructional design professionals who are aspiring to specialise in instructional design. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV. Enrol today and take the next step towards your personal and professional goals. 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 and Welcome to Curriculum Structural Design Start Here - Instructional Des 00:04:00 What Makes an Amazing Training Curriculum - Part 1 00:14:00 What Makes an Amazing Training Curriculum - Part 2 00:13:00 Identify With Your Audience Identify With Your Audience Introduction 00:05:00 Identify Their Roles 00:17:00 Identify Their Goals 00:09:00 Identify Their Why 00:18:00 Identify What They Do Identify What They Already Do 00:15:00 Identify What They Already Do Activity 00:18:00 Identify What They Want to Do 00:07:00 Identify What They Need to Do 00:09:00 Organize What They Do Organize What They Do Intro 00:07:00 Organize Tasks and Subtasks 00:19:00 Organize Tasks and Subtasks - Part 2 00:19:00 Create Modules and Lessons 00:16:00 Set Up a Curriculum Design Spreadsheet 00:20:00 Determine What to Teach Understanding Objectives 00:15:00 Understanding Objectives Activity 00:16:00 Determine Conventions to Teach 00:17:00 Determine Algorithms to Teach 00:17:00 Determine Concepts to Teach 00:17:00 Organize What to Teach Simplify and Group Objectives Part 1 00:06:00 Simplify and Group Objectives Part 2 00:17:00 Add Objectives to the Curriculum Design Spreadsheet 00:09:00 Mark Objectives For Assessments 00:11:00 Determine the Initial Class Structure Solidify Specific Course Groupings 00:15:00 Customize Course Titles and Lesson Titles 00:06:00 Determine Course Timelines 00:20:00 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

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Whether you're a beginner or a seasoned creator, this course is tailored to elevate your YouTube game and lead you toward exponential growth. 🚨 Limited Time Offer: Enroll now and gain access to exclusive bonuses, live Q&A sessions, and a vibrant community of like-minded creators eager to support your success! Don't let the ever-changing YouTube landscape intimidate you. Embrace the challenge, adapt, and thrive with our 'Succeeding in YouTube in the Current Landscape' course. Start your journey to YouTube stardom today! Course Curriculum Module 1: Discover The Complete Youtube Course For 2020!(Used When Combined With All Yt Courses) Discover The Complete Youtube Course For 2020!(Used When Combined With All Yt Courses) 00:00 Module 2: A Vision For Your Youtube! A Vision For Your Youtube! 00:00 Module 3: Remembering My First Video On Youtube Remembering My First Video On Youtube 00:00 Modue 4: Mrbeast Vs Me Mrbeast Vs Me 00:00 Module 5: Hardware For Filming Youtube Videos Hardware For Filming Youtube Videos 00:00 Module 6: Obs Vs Screenflow Vs Camtasia And Final Cut Pro X For Filming, Editing, And Rendering Videos! Obs Vs Screenflow Vs Camtasia And Final Cut Pro X For Filming, Editing, And Rendering Videos! 00:00 Module 7: Select Sensational Titles That Help Videos Go Viral And Or Optimize For Youtube Search! Select Sensational Titles That Help Videos Go Viral And Or Optimize For Youtube Search! 00:00 Module 8: How To Title Your Youtube Videos To Get More Views Secret Seo Strategy How To Title Your Youtube Videos To Get More Views Secret Seo Strategy 00:00 Module 9: Make Great Thumbnails Fast With Canva Even With No Graphic Design Experience! Make Great Thumbnails Fast With Canva Even With No Graphic Design Experience! 00:00 Module 10: How To Use The Youtube Creator Studio To Upload Videos In 2020 How To Use The Youtube Creator Studio To Upload Videos In 2020 00:00 Module 11: Publishing Schedule, Long-Term Viability, And Burn Out! Publishing Schedule, Long-Term Viability, And Burn Out! 00:00 Module 12: How To Make Money On Youtube With Ads, Memberships, Merchandise, And Super Chat How To Make Money On Youtube With Ads, Memberships, Merchandise, And Super Chat 00:00 Module 13: Sell Online Courses On Youtube With WordPress, Learndash, And Woocommerce Sell Online Courses On Youtube With WordPress, Learndash, And Woocommerce 00:00 Module 14: Get More Youtube Views And Make Sales With Google Ads! Get More Youtube Views And Make Sales With Google Ads! 00:00 Module 15: Being Grateful For Every Viewer! Being Grateful For Every Viewer! 00:00 Module 16: Coppa Everything You Need To Know - New Youtube Updates Make Compliance Easy Coppa Everything You Need To Know - New Youtube Updates Make Compliance Easy 00:00 Module 17: $10,000 A Day On Youtube $10,000 A Day On Youtube 00:00 Module 18: How To Grow With 288K Subscribers And 17,261,855 Youtube Views How To Grow With 288K Subscribers And 17,261,855 Youtube Views 00:00 Module 19: My 2019 Youtube Paycheck! How Much I Made On 1.3 Million Views + Secrets To Earn More Ad Revenue! My 2019 Youtube Paycheck! How Much I Made On 1.3 Million Views + Secrets To Earn More Ad Revenue! 00:00 Module 20: Easy Unique Content Idea Generation System For Bloggers And Youtubers Using Google Search Easy Unique Content Idea Generation System For Bloggers And Youtubers Using Google Search 00:00 Module 21: $53,802.38 Youtube Ad Revenue Earnings 2016 To 2019! See My Top 49 Videos! $53,802.38 Youtube Ad Revenue Earnings 2016 To 2019! See My Top 49 Videos! 00:00

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In this course, we will start with extremely basic concepts such as learning the programming language fundamentals and other supporting libraries. Then we will proceed with the core topics with the help of real-world datasets to gain a complete understanding of deep learning using Python and Keras.

Artificial neural networks (ANNs) are the most powerful machine learning algorithms available today. They are capable of learning complex relationships in data, and they have been used to achieve state-of-the-art results in a wide variety of fields, including image recognition, natural language processing, and speech recognition. The Future of Machine Learning is Here! This Project on Deep Learning - Artificial Neural Network course will teach you how to build and train ANNs from scratch. You will learn about the different components of an ANN, such as the input layer, hidden layers, and output layer. You will also learn about the different activation functions that can be used in ANNs, and you will see how to optimise ANNs for different tasks. In addition to the theoretical concepts, you will also get experience with ANNs. You will work on a project where you will build an ANN to classify images. You will use the TensorFlow library to build your ANN, and you will see how to train your ANN on a dataset of images. By the end of this Project on Deep Learning - Artificial Neural Network course, you will have a deep understanding of ANNs and how to use them. You will be able to build your own ANNs to solve a variety of problems. You will also be able to use the TensorFlow library to build and train ANNs. So what are you waiting for? Enrol in this course today and start learning about the future of machine learning!   Learning Outcomes: Through this comprehensive course, you should be able to: Understand the fundamental concepts of deep learning and artificial neural networks. Install and configure an artificial neural network framework. Preprocess and structure data for optimal model performance. Encode data effectively for neural network training and predictions. Build and deploy artificial neural networks for real-world applications. Address data imbalance challenges and optimise model accuracy.   Who is this course for? This Project on Deep Learning - Artificial Neural Network course is ideal for: Data scientists and machine learning practitioners seeking to expand their knowledge. Software engineers interested in leveraging deep learning techniques. Students pursuing a career in artificial intelligence and machine learning. Professionals looking to enhance their skills in neural network development. Individuals with a passion for exploring advanced machine learning techniques.   Career Path  Our course will prepare you for a range of careers, including: Deep Learning Engineer: £40,000 - £100,000 per year. Machine Learning Researcher: £45,000 - £120,000 per year. Data Scientist: £50,000 - £110,000 per year. Artificial Intelligence Specialist: £55,000 - £130,000 per year. Software Engineer (specialising in AI): £45,000 - £100,000 per year. Research Scientist (Machine Learning): £50,000 - £120,000 per year. AI Consultant: £60,000 - £150,000 per year. Certification After studying the course materials of the Project on Deep Learning - Artificial Neural Network (ANNs) there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Prerequisites This Project on Deep Learning - Artificial Neural Network (ANNs) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Project on Deep Learning - Artificial Neural Network (ANNs) 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.   Course Curriculum Section 01: Introduction Introduction of Project 00:03:00 Section 02: ANN Installation Setup Environment for ANN 00:11:00 ANN Installation 00:09:00 Section 03: Data Preprocessing Import Libraries and Data Preprocessing 00:11:00 Data Preprocessing 00:07:00 Data Preprocessing Continue 00:10:00 Section 04: Data Encoding Data Exploration 00:10:00 Encoding 00:07:00 Encoding Continue 00:06:00 Preparation of Dataset for Training 00:04:00 Section 05: Steps to Build ANN Steps to Build ANN Part 1 00:06:00 Steps to Build ANN Part 2 00:06:00 Steps to Build ANN Part 3 00:06:00 Steps to Build ANN Part 4 00:09:00 Section 06: Predictions and Imbalance-Learn Predictions 00:11:00 Predictions Continue 00:08:00 Resampling Data with Imbalance-Learn 00:09:00 Resampling Data with Imbalance-Learn Continue 00:08:00

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

This comprehensive course will help you learn how to use the power of Python to evaluate your deep learning-based recommender system data sets based on user ratings and choices with a practical approach to building a deep learning-based recommender system by adopting a retrieval-based approach based on a two-tower model.

Use deep learning, Computer Vision, and machine learning techniques to build an autonomous car with Python

The Computer Vision course with C++ and OpenCV with GPU support provides an introduction to computer vision and its applications using C++ and OpenCV with GPU acceleration. Students will learn about setting up the necessary environments, basic examples, background segmentation, object detection with OpenCV's ML module using C++ and CUDA, and optical flow. Learning Outcomes: Set up the required environments for C++ and OpenCV with GPU support. Understand the fundamentals of computer vision and its applications. Implement background segmentation techniques to extract relevant objects from the environment. Use OpenCV's ML module with C++ and CUDA to perform object detection efficiently. Apply optical flow algorithms to track object movements and analyze motion patterns. Why buy this Computer Vision: C++ and OpenCV with GPU support? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Computer Vision: C++ and OpenCV with GPU support there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Computer Vision: C++ and OpenCV with GPU support course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Computer Vision: C++ and OpenCV with GPU support does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Computer Vision: C++ and OpenCV with GPU support 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. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Computer Vision: C++ and OpenCV with GPU support is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 01: Set up Necesssary Environments Module 01: Driver installation 00:06:00 Module 02: Cuda toolkit installation 00:01:00 Module 03: Compile OpenCV from source with CUDA support part-1 00:06:00 Module 04: Compile OpenCV from source with CUDA support part-2 00:05:00 Module 05: Python environment for flownet2-pytorch 00:09:00 Unit 02: Introduction with a few basic examples! Module 01: Read camera & files in a folder (C++) 00:11:00 Module 02: Edge detection (C++) 00:08:00 Module 03: Color transformations (C++) 00:07:00 Module 04: Using a trackbar (C++) 00:06:00 Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++) 00:13:00 Unit 03: Background segmentation Module 01: Background segmentation with MOG (C++) 00:04:00 Module 02: MOG and MOG2 cuda implementation (C++ - CUDA) 00:03:00 Module 03: Special app: Track class 00:06:00 Module 04: Special app: Track bgseg Foreground objects 00:08:00 Unit 04: Object detection with openCV ML module (C++ CUDA) Module 01: A simple application to prepare dataset for object detection (C++) 00:08:00 Module 02: Train model with openCV ML module (C++ and CUDA) 00:13:00 Module 03: Object detection with openCV ML module (C++ CUDA) 00:06:00 Unit 05: Optical Flow Module 01: Optical flow with Farneback (C++) 00:08:00 Module 02: Optical flow with Farneback (C++ CUDA) 00:06:00 Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA) 00:05:00 Module 04: Optical flow with Nvidia Flownet2 (Python) 00:05:00 Module 05: Performance Comparison 00:07:00 Additional Resource Resources - Computer Vision: C++ and OpenCV with GPU support 00:00:00 Assignment Assignment - Computer Vision: C++ and OpenCV with GPU support 00:00:00

Welcome to this project-based course where you will build and deploy a realtor clone application using the latest version of React, Firebase, and Tailwind CSS. Learn to create and deploy a website professionally for showcasing to friends and clients, or adding it to your portfolio. Basic knowledge of HTML, CSS, and JavaScript is expected.