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Boost Your Career with Apex Learning and Get Noticed By Recruiters in this Hiring Season! Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now With a single payment you will gain access to Data Science Course Bundle 2022 including 10 Career development courses, original hardcopy certificate, transcript and a student ID card which will allow you to get discounts on things like music, food, travel and clothes etc. The world is one big data bank, and data science is one of the most demanding professional sectors of the present era. The analytical and programming-oriented field of data science has limited resources for candidates to learn and develop skills, which is why you need our highly advanced [course_title] course.With step-by-step interactive video content, our training will equip you with extensive knowledge and expertise in data science, including machine learning. This bundle course offers an opportunity to foster your career opportunities with an expert-level understanding of data science and become skilful in this industry. Take this course anywhere and at any time. Don't let your lifestyle limit your learning or your potential. Data Science Course Bundle 2022 will provide you with the CPD certificate that you'll need to succeed. Gain experience online and interact with experts. This can prove to be the perfect way to get noticed by a prospective employer and stand out from the crowd. Data Science Course Bundle 2022 has been rated and reviewed highly by our learners and professionals alike. We have a passion for teaching, and it shows. All of our courses have interactive online modules that allow studying to take place where and when you want it to. The only thing you need to take Data Science Course Bundle 2022 is Wi-Fi and a screen. You'll never be late for class again. Experienced tutors and mentors will be there for you whenever you need them, and solve all your queries through email and chat boxes. Benefits you'll get choosing Apex Learning for this Course: One payment, but lifetime access to 11 CPD courses Certificates, student ID for the title course included in a one-time fee Full tutor support available from Monday to Friday Free up your time - don't waste time and money travelling for classes Accessible, informative modules taught by expert instructors Learn at your ease - anytime, from anywhere Study the course from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills Gain valuable knowledge without leaving your home What other courses are included with this Course? Level 2 Microsoft Office Essentials Microsoft Teams Leadership & Management Diploma Working from Home Essentials Mental Health and Working from Home Online Meeting Management Effective Communication Skills Time Management Report Writing Emotional Intelligence and Human Behaviour Curriculum ***Data Science Course Bundle 2022*** Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview Set-up the Environment for the Course (lecture 1) Set-up the Environment for the Course (lecture 2) Two other options to setup environment Python Essentials Python data types Part 1 Python Data Types Part 2 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) Python Essentials Exercises Overview Python Essentials Exercises Solutions Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. NumPy arrays, built-in methods, array methods and attributes. Indexing, slicing, broadcasting & boolean masking Arithmetic Operations & Universal Functions Exercises Overview Exercises Solutions Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. Pandas Introduction Pandas Data Structures - Series Pandas Data Structures - DataFrame Handling Missing Data Data Wrangling - Combining, merging, joining Groupby Useful Methods and Operations Project 1 (Overview) Customer Purchases Data Project 1 (Solutions) Customer Purchases Data Project 2 (Overview) Chicago Payroll Data Project 2 (Solutions Part 1) Chicago Payroll Data Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach Matplotlib Essentials - Exercises Overview Matplotlib Essentials - Exercises Solutions Python for Data Visualization using Seaborn Introduction & Installation Distribution Plots Categorical Plots (Part 1) Categorical Plots (Part 2) Axis Grids Matrix Plots Regression Plots Controlling Figure Aesthetics Exercises Overview Exercise Solutions Python for Data Visualization using pandas Pandas Built-in Data Visualization Pandas Data Visualization Exercises Overview Panda Data Visualization Exercises Solutions Python for interactive & geographical plotting using Plotly and Cufflinks Interactive & Geographical Plotting (Part 1) Interactive & Geographical Plotting (Part 2) Interactive & Geographical Plotting Exercises (Overview) Interactive & Geographical Plotting Exercises (Solutions) Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types….. Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff Linear Regression Model - Hands-on (Part 1) Linear Regression Model Hands-on (Part 2) Good to know! How to save and load your trained Machine Learning Model! Linear Regression Model (Insurance Data Project Overview) Linear Regression Model (Insurance Data Project Solutions) Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificity…etc. Logistic Regression Model - Hands-on (Part 1) Logistic Regression Model - Hands-on (Part 2) Logistic Regression Model - Hands-on (Part 3) Logistic Regression Model - Hands-on (Project Overview) Logistic Regression Model - Hands-on (Project Solutions) Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality …. K Nearest Neighbors - Hands-on K Nearest Neighbors (Project Overview) K Nearest Neighbors (Project Solutions) Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging…. Decision Tree and Random Forests - Hands-on (Part 1) Decision Tree and Random Forests (Project Overview) Decision Tree and Random Forests (Project Solutions) Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) Support Vector Machines - Hands-on (SVMs) Support Vector Machines (Project 1 Overview) Support Vector Machines (Project 1 Solutions) Support Vector Machines (Optional Project 2 - Overview) Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method ….. K Means Clustering - Hands-on K Means Clustering (Project Overview) K Means Clustering (Project Solutions) Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) Principal Component Analysis (PCA) - Hands-on Principal Component Analysis (PCA) - (Project Overview) Principal Component Analysis (PCA) - (Project Solutions) Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance Python for Recommender Systems - Hands-on (Part 1) Python for Recommender Systems - - Hands-on (Part 2) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) NLP-Challenges, Data Sources, Data Processing ….. Feature Engineering and Text Preprocessing in Natural Language Processing NLP - Tokenization, Text Normalization, Vectorization, BoW…. BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes … Pipeline feature to assemble several steps for cross-validation… How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £10 * 11 = £110) Hard Copy Certificate: Free (For The Title Course) If you want to get hardcopy certificates for other courses, generally you have to pay £20 for each. But this Fall, Apex Learning is offering a Flat 50% discount on hard copy certificates, and you can get each for just £10! P.S. The delivery charge inside the U.K. is £3.99 and the international students have to pay £9.99. CPD 20 CPD hours / points Accredited by CPD Quality Standards Who is this course for? There is no experience or previous qualifications required for enrolment on this Data Science Course Bundle 2022. It is available to all students, of all academic backgrounds. Requirements Our Data Science Course Bundle 2022 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 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 this CPD certificate 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. Certificates Certificate of completion Digital certificate - Included

Description Explore the basics of typography for web and mobile UI to make your design powerful with the Level 3 Diploma in Typography for UI Designers course. The element of every layout is essential while designing a website. The course starts by explaining the typography terms and anatomy. You will learn to create amazing web and mobile app design by using meaningful fonts. The use of fonts, line-height and letter spacing, Google android typography, using Vertical Rhythm in Bootstrap will be discussed here. Then you will learn to balance balancing your design by using LEGO Blocks method. Finally, the procedures for connecting your Photoshop Screen to iPhone or Android Device, and many other essential concepts will be reviewed in the course. Shortly, the course covers the concepts of Font Pairing, Web Typography, App Typography & Vertical Rhythm. Entry Requirement: NOT for Novices (Must have some Photoshop Experience) Web Designers Mobile App Designers All Designers who think their design have something missing Web Developers Graphic Designer 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 completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. 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 After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Introduction to Typography 1.2.Intro to typography course 00:05:00 1.3. how typography cousre is laid out 00:02:00 1.4.What are Font Families 00:05:00 1.5.typography-antomy-terms 00:07:00 1.6.Humanist Old and Transitional 00:07:00 1.7.Sans-Serif Script Other Sans 00:06:00 1.8. Line-length in Typography 00:03:00 1.9.Alignments of your text 00:05:00 1.10.Line-height matters 00:07:00 1.11.Letter Spacing kerning 00:05:00 1.12.exercise to apply all we learned 00:11:00 More about Typography 2.1.Different Types of Hyphens & Dashes 00:02:00 2.2. About Quotation Marks 00:03:00 Typography Scales and Grids 3.1.1Expanding Scales-NEW 00:07:00 3.1.Roles Of Typefaces-1 00:05:00 3.2.Typography Scale-1 00:03:00 3.3Type Hierarchy Online Tools 00:05:00 3.4.How Many Levels Of Hierarchy-update 00:03:00 3.5.Vertical Rhythm-updated 00:05:00 3.6.Vertical Rhythm In Photoshop 00:07:00 3.7.exercise Vertical Rhythm-1 00:12:00 3.8.modular Grid 00:11:00 EXERCISES: Modular + Baseline Grid Design Ultimate Exericse 4.1.prepare Modular Grid For Design Exericse 00:11:00 4.2.Modular Design part 1 00:16:00 4.3.Modular design 2nd 00:10:00 4.4.Modular Design Refining the design 00:03:00 4.5.Modulr Design 3rd Layout 00:10:00 How to Select Fonts? 5.1.how Many Fonts 00:05:00 5.2.Moods Voices Of Typefaces- 00:13:00 5.3.colors Efffect On Typo 00:04:00 How to Pair Fonts? 6.1.Font Pairing Intro-Updated 00:04:00 6.2.X-height Matching 00:05:00 6.3.Contrast Matching 00:10:00 6.4.Look For Similar Features 00:10:00 6.5.Avoid Too Similarity 00:04:00 6.6.Pairing Fonts Same Family Designer 00:05:00 6.7.Online Tools Font Pairing 00:06:00 How to get Variation in text for Great Designs 7.1.variation with bold italic 00:04:00 7.2.variation with colors 00:03:00 7.3.Variation with Reverse-colors updated- 00:03:00 7.4.variation with lineheight 00:04:00 EXERCISES: Dribbble LEVEL Designs 8.1. Dribbble Hero Design preperation 00:05:00 8.2.dribbble Hero Design V1 Part 1 00:16:00 8.3.dribbble Hero Design V1 Part 2 00:16:00 8.4. Dribbble Hero Variation Intro 00:04:00 8.5. Dribbble Hero Variation 2 Part 1 00:08:00 8.6. Dribbble Hero Variation 2 Part2 00:06:00 Exercise: Social Media Ad Design with 3 different fonts 9.1.summer Discount Ad DesignPreperations 00:04:00 9.2 Preparing base of design 00:07:00 9.3. Adding Text and styles 00:14:00 9.4.final Adjustments 00:03:00 Nature Health Themed Typography Exercises 10.1.juicy Design Exercise Preperations-1 00:03:00 10.2.making Of Juicy Design-2 00:16:00 10.3.juicy Designs Final-3 00:12:00 Typography for Iphone and Android App Designs (Mobile App Typography) 11.1 Intro IOS point sizing 00:05:00 11.2.IOS Font Specs 00:03:00 11.3.Designing multiple IOS Screens 00:14:00 11.4. Student Question About Resoltutions 00:14:00 11.5.connect Your Iphone With Photoshop 00:05:00 11.6. Android Typography 00:04:00 11.7.android Design Exercise For All Sizes 00:09:00 Typography for Web Developers 12.1.Using Google Fonts 00:04:00 12.2.using Premium Fonts 00:06:00 12.3.Intro to css font sizigin 00:03:00 12.4.what Is Em Font Size 00:08:00 12.5.What is rem font size 00:05:00 12.6.How percentage font size works 00:04:00 12.7.How vw font unit works 00:04:00 Responsive Typography for Developers 13.1.how Vertical Rhythm Works In CSS 00:08:00 13.2.Gridlover Exercise 00:08:00 13.3.custom Typographic Scale Boostrap-3 00:13:00 13.4.dont Use Code From Typescale 00:02:00 New and Latest in Typography 14.1.responsive Typography Intro 00:07:00 14.2.different Ratios And Scales In Responsive Typography 00:10:00 14.3.percentage Value Technique For Responsive Type 00:12:00 15.1 Color Fonts 00:05:00 15.2 variable-fonts101 00:08:00 Mock Exam Final Exam Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Duration 4 Days 24 CPD hours Overview By the end of the course, you should be able to meet the following objectives: Describe how Tanzu Kubernetes Grid fits in the VMware Tanzu portfolio Describe the Tanzu Kubernetes Grid architecture Deploy and manage Tanzu Kubernetes Grid management and supervisor clusters Deploy and manage Tanzu Kubernetes Grid workload clusters Deploy, configure, and manage Tanzu Kubernetes Grid packages Perform basic troubleshooting During this four-day course, you focus on installing VMware Tanzu© Kubernetes Grid? in a VMware vSphere© environment and provisioning and managing Tanzu Kubernetes Grid clusters. The course covers how to install Tanzu Kubernetes Grid packages for image registry, authentication, logging, ingress, multipod network interfaces, service discovery, and monitoring. The concepts learned in this course are transferable for users who must install Tanzu Kubernetes Grid on other supported clouds. Course Introduction Introductions and course logistics Course objectives Introducing VMware Tanzu Kubernetes Grid Identify the VMware Tanzu products responsible for Kubernetes life cycle management and describe the main differences between them Explain the core concepts of Tanzu Kubernetes Grid, including bootstrap, Tanzu Kubernetes Grid management, supervisor, and workload clusters List the components of a Tanzu Kubernetes Grid instance VMware Tanzu Kubernetes Grid CLI and API Illustrate how to use the Tanzu CLI Define the Carvel Tool set Define Cluster API Identify the infrastructure providers List the Cluster API controllers Identify the Cluster API custom resource definitions Authentication Explain how Kubernetes manages authentication with Management clusters Explain how Kubernetes manages authentication with supervisor clusters Define Pinniped Define Dex Describe the Pinniped authentication workflow Load Balancers Illustrate how load balancing works for the Kubernetes control plane Illustrate how load balancing works for application workload Explain how Tanzu Kubernetes Grid integrates with VMware NSX Advanced Load Balancer List load balancing options available on public clouds VMware Tanzu Kubernetes Grid on vSphere List the requirements for deploying a supervisor cluster List the steps to install a Tanzu Kubernetes Grid supervisor cluster Summarize the events of a supervisor cluster creation List the requirements for deploying a management cluster List the steps to install a Tanzu Kubernetes Grid management cluster Summarize the events of a management cluster creation Demonstrate how to use commands when working with management clusters VMware Tanzu Kubernetes Grid on Public Clouds List the requirements for deploying a management cluster on AWS and Microsoft Azure List the configuration options to install a Tanzu Kubernetes Grid a management cluster on AWS and Azure Tanzu Kubernetes Workload Clusters List the steps to build a custom image Describe the available customizations Identify the options for deploying Tanzu Kubernetes Grid clusters Explain the difference between the v1alpha3 and v1beta1 APIs Explain how Tanzu Kubernetes Grid clusters are created Discuss which VMs compose a Tanzu Kubernetes Grid cluster List the pods that run on a Tanzu Kubernetes Grid cluster Describe the Tanzu Kubernetes Grid core add-ons that are installed on a cluster Tanzu Kubernetes Grid Packages Define the Tanzu Kubernetes Grid packages Explain the difference between Auto-Managed and CLI-Managed packages Define packages repositories Configuring and Managing Tanzu Kubernetes Grid Operation and Analytics Packages Describe Cert-Manager Describe the Harbor Image Registry Describe Fluent Bit Identify the logs that Fluent Bit collects Explain basic Fluent Bit configuration Describe Prometheus and Grafana Configuring and Managing Tanzu Kubernetes Grid Networking Packages Describe the Contour ingress controller Demonstrate how to install Contour on a Tanzu Kubernetes Grid cluster Describe ExternalDNS Demonstrate how to install Service Discovery with ExternalDNS Describe Multus CNI Tanzu Kubernetes Grid Day 2 Operations List the load balancer configuration options in vSphere to load balance applications Demonstrate how to configure Ingress with the NodePortLocal Mode Explain how to install VMware Tanzu Application Platform Describe life cycle management in Tanzu Kubernetes Grid Explain how backup and restore are implemented in Tanzu Kubernetes Grid Describe Velero and Restic List the steps to back up a Workload cluster using Velero and Restic Troubleshooting Tanzu Kubernetes Grid Discuss the various Tanzu Kubernetes Grid logs Identify the location of Tanzu Kubernetes Grid logs Explain the purpose of crash diagnostics Demonstrate how to check the health of a Tanzu Kubernetes Grid cluster Explain packages cleanup procedures Explain management recovery procedures Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Tanzu Kubernetes Grid: Install, Configure, Manage [V2.0] 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 VMware Tanzu Kubernetes Grid: Install, Configure, Manage [V2.0] 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 Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis 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? 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 for Data Analysis. It is available to all students, of all academic backgrounds. Requirements Our Python for Data Analysis 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 19 sections • 99 lectures • 00:08:00 total length •Welcome & Course Overview: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:37:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method ..: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00 •Resources- Python for Data Analysis: 00:00:00

Duration 3 Days 18 CPD hours This course is intended for The intended audience for this course is experienced web developers who are new to User Experience (UX) and Responsive Design principles. These professionals typically have a solid understanding of front-end development technologies such as HTML, CSS, and JavaScript but seek to expand their skillset to create more user-centric, adaptable, and accessible web experiences. Roles that would benefit from this course include: Front-end Web Developers Full-stack Developers Web Designers Team Leads and Project Managers Freelance Web Developers Overview Working in a hands-on learning environment led by our expert UX coach, you'll learn to: Understand and apply UX principles and user-centered design processes: Participants will learn to identify the needs and preferences of users, create user personas, and apply UX best practices to develop intuitive, user-friendly web experiences. Design and implement responsive web layouts: Participants will gain the skills to create fluid grid layouts, use flexible images, and apply media queries to design web pages that adapt seamlessly across various devices and screen sizes. Optimize web performance for responsive designs: Participants will learn techniques to improve website performance, including image optimization, responsive images, and minification and concatenation of assets, ensuring a fast and smooth user experience across devices. Implement accessible web designs: Participants will understand the importance of accessibility in web design and learn to apply WCAG principles and accessible design patterns to create websites that are usable by a wide range of users, including those with disabilities. Collaborate effectively with designers, developers, and stakeholders: Participants will gain insights into design collaboration and handoff processes, enhancing their ability to communicate design decisions, provide and receive feedback, and work efficiently with team members and clients. In today's fast-paced digital world, user-centric and adaptable websites are no longer a luxury ? they're a necessity. By embracing UX and responsive design, you'll unlock the potential to elevate your websites, boosting user satisfaction and engagement. This, in turn, leads to higher conversion rates and a stronger online presence for your clients or organization, as well as better collaboration within your team, bridging the gap between designers, developers, and stakeholders.UX Design & Responsive Design for Experienced Web Developers is a three day, engaging hands-on workshop designed to equip you with the latest skills and best practices in User Experience (UX) and Responsive Web Design required to create seamless, user-friendly websites that adapt effortlessly across devices. This course will immerse you in the latest skills, best practices, and hands-on activities, empowering you to create exceptional, accessible websites that excel across devices and captivate users. Throughout the program you?ll explore the fundamentals of UX and responsive design, including user-centered design processes, mobile-first and desktop-first approaches, and design techniques for various devices and screen sizes. You'll gain practical experience creating responsive layouts, optimizing performance, and implementing accessible web designs, all while leveraging popular frameworks and design tools. You'll also gain valuable insights into performance optimization, accessibility, and collaboration strategies, ensuring you have the complete toolkit to excel in your field.By the end of this workshop, you?ll have gained a solid understanding of UX and responsive design principles, as well as hands-on experience in applying these concepts to real-world projects. You?ll be able to create more user-friendly, responsive, and accessible websites, and collaborate more effectively with your design and development teams. Introduction to UX and Responsive Design: Understanding User Experience What is UX? Importance of UX in web development UX principles and best practices User-centered design process Responsive Web Design Basics What is Responsive Web Design? Importance of Responsive Design in modern web development Fluid grid layout, flexible images, and media queries Hands-on Activity: Creating a Responsive Layout Designing a simple responsive layout using HTML, CSS, and media queries Breakdown and explanation of the code Testing responsiveness across different devices Mobile-first vs. Desktop-first Approaches Pros and cons of each approach Deciding which approach to use Designing for Different Devices and Screen Sizes Common breakpoints and device considerations Accessibility and usability across devices Typography, color, and other design elements in responsive design Hands-on Activity: Designing for Different Devices Modifying the previously created responsive layout to optimize for various devices Discussion and feedback on designs Advanced UX and Responsive Design Techniques: UX Research and Testing Importance of UX research Usability testing and user feedback A/B testing and heatmaps Navigation and Information Architecture Designing effective and user-friendly navigation Organizing content and information Common navigation patterns in responsive design Hands-on Activity: Designing Navigation for Responsive Websites Adding navigation elements to the previously created responsive layout Testing navigation on different devices and screen sizes Discussion and feedback on navigation designs Responsive Web Design Frameworks and Tools Overview of popular frameworks (Bootstrap, Foundation, etc.) Pros and cons of using frameworks Introduction to design tools (Sketch, Figma, Adobe XD) Hands-on Activity: Exploring Frameworks and Tools Experimenting with a chosen framework or design tool Redesigning the responsive layout using the selected framework/tool Sharing experiences and discussing the benefits and drawbacks UX and Responsive Design Best Practices: Design Patterns and UI Components Common design patterns in responsive web design Designing reusable UI components Consistency and usability in UI components Performance Optimization Importance of performance in responsive design Image optimization and responsive images Minification and concatenation of assets Hands-on Activity: Optimizing Performance (1.5 hours) Applying performance optimization techniques to the responsive layout Testing the improvements in performance Sharing results and discussing best practices Accessibility in UX and Responsive Design Importance of accessibility in web design Accessibility principles (WCAG) Accessible design patterns and techniques Hands-on Activity: Evaluating and Improving Accessibility Assessing the accessibility of the responsive layout Implementing accessibility improvements Testing and discussing the results Design Collaboration and Handoff Collaborating with designers, developers, and stakeholders Effective communication and documentation Design handoff tools and techniques Hands-on Activity: Simulating Design Handoff Participants will work in pairs to simulate a design handoff Reviewing, discussing, and providing feedback on each other's responsive layouts Sharing experiences and lessons learned

Overview In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol 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? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. 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 Course Curriculum 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:17:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method.: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00

With this course, you will master all CloudFormation concepts, and become confident in writing CloudFormation templates using YAML. Throughout the course, you will encounter various interesting examples and activities that will help you to consolidate your learning.

A beginner-level course loaded with JavaScript coding examples so that you can learn the fundamentals of JavaScript code. Explore the fundamental core concepts of using JavaScript and how to apply JavaScript code to create interactive web applications with the help of this carefully structured course. The fundamentals of JavaScript are all you need to start coding today and build amazing things with JavaScript.

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