4115 Computing courses in Dunstable delivered On Demand

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

This course covers the basic concepts of machine learning (ML) that are crucial for getting started on the journey of becoming a skilled ML developer. You will become familiar with different algorithms and networks, such as supervised, unsupervised, neural networks, Convolutional Neural Network (CNN), and Super-Resolution Convolutional Neural Network (SRCNN), needed to develop effective ML solutions.

Linux Troubleshooting and Administration

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.

If you know various DevOps tools such as Git, Jenkins, Maven, Ansible, Docker, and Kubernetes, and are not sure how they work collaboratively, then this course is for you. Learn to create a simple DevOps project using Git as the local version control system, GitHub as the distributor version control system, Jenkins as the continuous integration tool, Maven as a build tool, Ansible as configuration management and deployment tool, Docker for containerization, Kubernetes as a container management tool, and all this environment is set up on AWS.

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 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: 00:04:00 •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: 00:06:00 •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 Statistics Essentials will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Statistics Essentials comes with accredited certification, 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? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Statistics Essentials. It is available to all students, of all academic backgrounds. Requirements Our Statistics Essentials 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 11 sections • 11 lectures • 02:19:00 total length •Introduction to Statistics: 00:18:00 •Measuring Central Tendency: 00:18:00 •Measures of Dispersion: 00:11:00 •Correlation and Regression Analysis: 00:14:00 •Probability: 00:16:00 •Sampling: 00:19:00 •Charts and Graphs: 00:21:00 •Hypothesis Testing: 00:10:00 •Ten Common Statistical Mistakes: 00:12:00 •Assignment - Statistics Essentials: 00:00:00 •Order Your Certificate: 00:00:00

Some sources estimate that up to 91% of cyber security breaches begin with email scams, also known as phishing. While these types of attacks have been around for decades, they are becoming more common and more dangerous due to the growing sophistication of cyber criminals and their ability to trick employees. However, with the proper training, everyone in your organization can learn to identify phishing and protect your company from costly attacks. Our four-part series on phishing covers what a phishing attack is, how to quickly recognize one, rules for protecting yourself and your organization, and how to respond to an attempted attack. Learning Objectives Recognize the red flags and common tactics used in email-based phishing attacks, enabling you to identify and avoid potential threats.;Discover best practices for handling suspicious emails and social media-based phishing scams.;Gain insights into the importance of employee awareness and vigilance in preventing phishing attacks, ensuring your organization remains a challenging target for cybercriminals.

🌟 Introducing 'Skills for Role Playing Games'   Embark on a journey to master the art of Role Playing Games (RPGs) with our comprehensive training program. Whether you're a novice seeking to delve into the immersive worlds of RPGs or a seasoned player aiming to refine your skills, our modules are designed to elevate your gameplay experience to new heights.   📘 Module 1: Introduction to Role Playing Games Get acquainted with the fundamentals of RPGs, from understanding game mechanics to exploring different genres and playstyles. Lay the groundwork for your adventure and unlock the secrets of successful role-playing.   🌍 Module 2: World Building and Lore Dive deep into the creation of captivating game worlds and rich lore. Learn the art of building immersive environments, crafting compelling backstories, and developing intricate cultures that will enchant players and breathe life into your game universe.   🎭 Module 3: Character Design and Progression Master the art of character creation and development. Discover the key elements of designing memorable characters, from personalities to abilities, and learn how to guide their growth throughout the game, ensuring a dynamic and engaging player experience.   📜 Module 4: Quest Design and Narrative Crafting Unleash your creativity as you delve into the intricacies of quest design and storytelling. Explore techniques for crafting captivating narratives, designing challenging quests, and weaving them seamlessly into the fabric of your game world to immerse players in unforgettable adventures.   🤝 Module 5: Player Interaction and Dynamic NPCs Explore the dynamics of player interaction and the role of Non-Player Characters (NPCs) in shaping the gaming experience. Learn how to create dynamic NPCs with distinct personalities and motivations, fostering meaningful interactions that enhance immersion and engagement.   🌐 Module 6: World Events and Dynamic Storytelling Unlock the power of dynamic storytelling and world events to keep players engaged and invested in your game world. Discover how to create dynamic events that evolve based on player actions, driving the narrative forward and ensuring a constantly evolving gaming experience.   🚀 Why Choose 'Skills for Role Playing Games'? Comprehensive training covering all aspects of RPG design and gameplay. Expert-led modules crafted by industry professionals with years of experience. Practical insights and hands-on exercises to reinforce learning. Suitable for beginners and seasoned players alike, catering to diverse skill levels. Elevate your game design and storytelling abilities to create unforgettable RPG experiences.   Don't just play RPGs - master them with 'Skills for Role Playing Games' and unlock the potential to create worlds that captivate players and stand the test of time. Enroll now and embark on your journey to RPG mastery! Course Curriculum Module 1_ Introduction to Role Playing Games Introduction to Role Playing Games 00:00 Module 2_ World Building and Lore World Building and Lore 00:00 Module 3_ Character Design and Progression Character Design and Progression 00:00 Module 4_ Quest Design and Narrative Crafting Quest Design and Narrative Crafting 00:00 Module 5_ Player Interaction and Dynamic NPCs Player Interaction and Dynamic NPCs 00:00 Module 6_ World Events and Dynamic Storytelling World Events and Dynamic Storytelling 00:00