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In this Advanced Diploma in User Experience UI/UX Design course, you will learn everything you need to know to become an expert UI/UX designer. We will start by teaching you the basics of UX and UI design and then move on to more advanced topics like wireframing prototyping, and usability testing. We will also teach you how to use Adobe XD, a powerful design tool professionals use worldwide. UI/UX design is the process of creating products that are user-centred. It is all about understanding user demands and building goods to fulfil those goals. This User Experience Design course will begin with an overview of the web industry, with an emphasis on essential concepts and trends. You will then learn about the fundamentals of graphic design, understanding the principles and techniques that underpin visually appealing designs. You will explore the exciting world of UX design with a solid foundation, concentrating on building user-centred experiences that meet users' requirements and aspirations. The course will also teach you how to integrate your UX design thoughts into aesthetically appealing user interfaces. To bring your ideas to life, you will use Adobe XD, a sophisticated design tool. You will find optimisation tactics along the way to improve the performance and usability of your designs. Furthermore, this course offers useful insights on how to begin a career in UI/UX design, as well as resources and support to help you excel in the sector. Practical assignments will allow you to put your newly learned abilities to use and receive feedback, ensuring that you obtain experience throughout your learning journey. Join us in the User Experience Design from A-Z: Adobe XD UI/UX Design course to realise your full potential as a UI/UX designer. Begin by developing memorable and user-friendly digital experiences that engage users and create a lasting impression. Enrol now and start your path to a successful career in UI/UX design! Learning Outcomes: Upon completion of the User Experience Design course, you will be able to: Understand the main concepts and trends in the web industry. Apply the principles of graphic design to create visually appealing designs. Properly design user-centred experiences that meet users' needs and goals. Translate UX design concepts into visually engaging user interfaces. Utilise Adobe XD to bring your designs to life with interactive prototypes. Optimise designs for improved performance and usability. Gain valuable insights and resources for starting a career in UX/UI design. Who is this course for? This User Experience Design course is ideal for: Beginners interested in entering the UX/UI design field. Graphic designers looking to expand their skill set into UX/UI design. Web designers seeking to enhance their understanding of user experience. Product managers and developers aiming to collaborate effectively with designers. Individuals passionate about creating intuitive and impactful digital experiences. Career Path  Our course will prepare you for a range of careers, including: Junior UX/UI Designer: £25,000 - £40,000 per year. UX/UI Designer: £35,000 - £70,000 per year. Senior UX/UI Designer: £50,000 - £100,000 per year. UX/UI Design Lead: £80,000 - £90,000 per year. UX/UI Design Manager: £95,000 - £120,000 per year. UX/UI Design Director: £120,000+ per year. Certification After studying the course materials of the Advanced Diploma in User Experience UI/UX Design 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 Advanced Diploma in User Experience UI/UX Design does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in User Experience UI/UX Design 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 UX/UI Course Introduction Learn UX/UI Course Overview 00:05:00 Section Overview 00:04:00 UX vs UI 00:04:00 UX/UI Designer Marketplace 00:05:00 Overview of UX Roles 00:06:00 Introduction To The Web Industry Web Industry Section Overview 00:03:00 The Phases of Web Development 00:13:00 Designer Responsibilities (working in a team) 00:09:00 Roles & Descriptions (working in a team) 00:05:00 Agile Approach To Project Management 00:12:00 Scrum - Flexible Framework 00:06:00 Project Management Apps 00:13:00 XD Lesson - Introduction 00:13:00 Foundations of Graphic Design Graphic Design Section Overview 00:02:00 The Psychology of Color 00:13:00 Color Wheel & Color Schemes 00:06:00 Working with Fonts 00:10:00 Working With Icons 00:04:00 XD Lesson - Tools, Object Manipulation and Components 00:13:00 XD Lesson - Font Styles and Artboard Settings 00:07:00 Graphic Design Software Tools 00:03:00 Adobe XD lesson 4 - Icons & Vector Graphics 00:14:00 UX Design (User Experience Design) UX Design Section Overview 00:04:00 What is User Experience Design? (UX) 00:09:00 UX Design Process 00:03:00 The UX Analysis Process 00:08:00 Working with User Profiles 00:03:00 Understanding User Pain Points 00:03:00 XD Lesson 5 Class Project: Сompetitive Analysis 00:10:00 Developing a Persona Part 1 00:05:00 Developing a Persona Part 2 00:05:00 Customer Journey 00:04:00 Customer Journey vs Sales Funnel 00:04:00 3 Phases of a Sales Funnel 00:07:00 4 Stages of a Sales Funnel 00:06:00 Macro/Micro Conversions 00:05:00 Stages of Market Sophistication 00:06:00 Lead Generation Funnel 00:06:00 Digital Product Sales Funnel 00:05:00 7 Principles of Influence 00:12:00 Age Based Influence Triggers 00:06:00 Gender Influence Triggers 00:06:00 Interest Based Marketing 00:04:00 Understanding User Flow 00:08:00 XD Lesson 6 Class Project: Userflow - Your first UX deliverable 00:07:00 Working with Story Boards 00:05:00 XD Lesson 7 Class Project: Crafting a Story board 00:09:00 Working with Moodboards 00:04:00 XD Lesson 8 Class Project: Creating Moodboard 00:11:00 Sitemap & Information Architecture 00:07:00 XD Lesson - Class Project: App Architecture 00:09:00 Low and Hi Fidelity Wireframes 00:03:00 XD Lesson - Class Project: Login Screen Wireframe Using Material Design 00:08:00 Working with Prototypes 00:04:00 XD Lesson - Class Project: Home Screen Wireframe and Linking 00:07:00 XD Lesson - Class Project: Adding Interaction to Wireframes 00:10:00 Testing and Evaluating 00:11:00 UX Deliverables 00:03:00 UX Design Conclusion 00:01:00 UI Design (User Interface Design) UI Design Section Overview 00:03:00 UI Design Overview 00:03:00 Types of Interfaces 00:10:00 Landing Pages Overview 00:10:00 XD Lesson - Using Grids in XD 00:08:00 XD Lesson - Single Card design 00:13:00 UI Controls 00:07:00 UI Navigational Components 00:12:00 Header Design Overview 00:07:00 XD Lesson - Mobile & Desktop: Header Design 00:10:00 XD Lesson - Mobile & Desktop: Dropdown Design 00:06:00 Common Layouts Overview 00:08:00 XD Lesson - Common Layouts 00:07:00 Mobile & Desktop Footer Design Overview 00:07:00 XD Lesson - Mobile & Desktop: Footer Design 00:06:00 Mobile & Desktop Button Design Overview 00:05:00 XD Lesson - Mobile & Desktop: Button Design 00:10:00 XD Lesson - Mobile & Desktop: Input Design 00:07:00 Mobile & Desktop Filter Search Bar Design Overview 00:06:00 Adobe XD Lesson - Mobile & Desktop: Filter Design 00:07:00 Adobe XD Lesson - Mobile & Desktop: Search Design 00:03:00 UI Kit Overview 00:05:00 Adobe XD Lesson - Desktop and Mobile: UI Kit 00:06:00 Microinteractions Overview 00:05:00 Adobe XD lesson - Microinteractions 00:07:00 Optimization Optimization Section Overview 00:02:00 Feedback Review & Getting Referrals 00:04:00 'Above the Fold' Rule 00:04:00 Adobe XD lesson - Designing a Powerful Above the Fold 00:08:00 Using Analytics For Optimization 00:05:00 Heat Maps & Element Placements 00:04:00 Crafting A Usability Report Overview 00:08:00 Adobe XD lesson - Crafting Reports in XD 00:20:00 Starting a Career in UX/UI Design Careers in UX/UI Section Overview 00:06:00 Your Daily Productivity Hub 00:14:00 How To Start Freelancing 00:08:00 Client Consulting 00:04:00 Building a Brand 00:10:00 Personal Branding 00:06:00 The Importance of Having a Website 00:08:00 Creating a Logo 00:05:00 Step by Step Website Setup 00:17:00 UI Templates 00:06:00 Logo Templates 00:04:00 Creating a Business Email 00:06:00 Networking Do's and Don'ts 00:04:00 Top Freelance Websites 00:10:00 UX/UI Project Scope Questions 00:10:00 Laser Focus & Productivity Tools 00:06:00 The Places to Find UX Jobs 00:05:00 Resources Resources - Advanced Diploma in User Experience UI/UX Design 00:00:00 Assignment Assignment - Advanced Diploma in User Experience UI/UX Design 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up 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 Essentials 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 Python for Data Analysis using NumPy 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 Python for Data Analysis using Pandas 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 Python for Data Visualization using matplotlib 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 Python for Data Visualization using Seaborn 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 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks 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 Capstone Project - Python for Data Analysis & Visualization 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 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model 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 Python for Machine Learning - scikit-learn - Logistic Regression Model 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 Python for Machine Learning - scikit-learn - K Nearest Neighbors 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 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests 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 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) 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 Python for Machine Learning - scikit-learn - K Means Clustering 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 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) 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 Recommender Systems with Python - (Additional Topic) 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 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) 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 Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content Welcome, Course Introduction & overview, and Environment set-up 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 Essentials 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 Python for Data Analysis using NumPy 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 Python for Data Analysis using Pandas 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 Python for Data Visualization using matplotlib 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 Python for Data Visualization using Seaborn 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 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks 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 Capstone Project - Python for Data Analysis & Visualization 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 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model 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 Python for Machine Learning - scikit-learn - Logistic Regression Model 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 Python for Machine Learning - scikit-learn - K Nearest Neighbors 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 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests 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 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) 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 Python for Machine Learning - scikit-learn - K Means Clustering 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 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) 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 Recommender Systems with Python - (Additional Topic) 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 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) 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 Resources - Data Science and Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

In the first part of the workshop, Sophia will explain the brain processes during the creative process and Bianca will provide us with practical tips by introducing us to her Two Can Do Method which is also based on neuroscience and other disciplines.

What is dance psycholgy? Why does it matter? And what you as a dancer, dance teacher should defintely know about it to better improve mental well-being? All these questions will be answered in this workshop who will introduce you to dance psychology and its key aspects. The workshop will be recorded for those who cannot attend.

About Course ASP.NET Core MVC 6: Master the Latest Web Development Framework Become a full-stack web developer with this comprehensive course on ASP.NET Core MVC 6, taught by a lead instructor with 20+ years of experience. This course is designed for beginners with zero or basic programming experience. You will learn everything you need to know to build modern web applications with ASP.NET Core MVC 6, including: HTML5 and CSS3 Bootstrap 4 C# ASP.NET Core MVC 6 Entity Framework Core SQL Server Express You will also learn about important web development concepts such as routing, controllers, views, and models. The course includes HD video tutorials, code challenges, and coding exercises to help you learn and practice the material. You will also build a real-world project to apply your skills. By the end of this course, you will be fluent in ASP.NET Core MVC 6 and ready to build any website you can dream of. Enroll today and start your journey to becoming a full-stack web developer! Benefits of taking this course: Learn from a lead instructor with 20+ years of experience Become a full-stack web developer with just one course Learn the latest tools and technologies used at large companies such as Apple, Facebook, Google, and Netflix Get comprehensive student testing and feedback from students who are working and applying these coding examples Learn by building real-world websites and web apps Get access to HD video tutorials, code challenges, and coding exercises Target audience: Beginners with zero or basic programming experience who want to learn how to build modern web applications with ASP.NET Core MVC 6 What Will You Learn? Learn structure of ASP .NET MVC Core (.NET 6) Project Create websites and webapp for your business needs Get a job as a junior web developer on Microsoft technologies Identify a case study to manage a project development Master front-end development using HTML & CSS back-end development using C# & MS SQL Create fully function dynamic MVC Core web applications using Asp .NET Core Creating Functional Model, View and Controller functionality on Movie Project Learn to Add Entity Framework Packages to Project Using NuGet Package Manager Applying SQL Server Database Connection to your application Running Power Shell Commands for Scaffolding and CRUD function Webforms Identify and applying Database Migrations You will learn fully functional Validations for your project Course Content Getting Started Course Introduction Course Curriculum How to Get Course Requirements Getting Started on Windows, Linux or Mac How to Ask Great Questions FAQ's ASP.NET Basics Section Introduction What You Can Build with ASP.NET Core What is ASP.NET Core How to Get Visual Studio Installing Visual Studio and ASP.NET Creating New Project Summary Prerequisites: HTML, CSS and Bootstrap Section Introduction HTML Overview Paragraph HTML List Items Forms CSS Overview CSS Internal CSS External CSS Forms Bootstrap Overview First Bootstrap Website Bootstrap Grids System Bootstrap Cards Summary ASP.NET MVC: Movie Project Section Introduction Source Code Reference MVC - Model View Controller Create a MVC Project Exploring the MVC Template Creating Controller Add a Controller URL Routing Logic Creating View Add a View Change Views and Layout Pages Passing Data from Controller to View Creating Model Add a Model Add Entity Framework Packages Scaffold Movie Pages-CRUD Database Migrations Initial Migration Generated Database Context Class Dependency Injection Database Connection String Summary Working with Database Section Introduction SQL Server Express Local DB Seed the Database Add the Seed Initializer Summary Add Search to ASP.NET Core MVC App Section Introduction Add Search Method to Controller Add Search to Page Search by Parameter Summary Model Update Section Introduction Add a New Field to Model Add-Migration Update Database Summary Validations Add Validation Rules to Model Required and Minimum Length Regular Expression Range String Length Validation on Error UI Enable JavaScript on Browser Examine the Details and Delete Code Review on Details Method Code Review on Delete Method Course Files and Resources Course Files and Resources A course by Sekhar Metla IT Industry Expert Xpert Learning RequirementsBasic C# programming experience needed(optional). You will learn MVC Core need to knowNo software is required in advance of the course (all software used in the course is free)No pre-knowledge is required on MVC - you will learn from basic Audience Beginner Asp .Net MVC Core C# coding, Microsoft SQL and CSS developers curious about web development Anyone who wants to generate new income streams Anyone who wants to build dynamic web applications Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Anyone who wants to become a Full stack web developer Anyone who wants to build fully functional asp .net core mvc database applications Audience Beginner Asp .Net MVC Core C# coding, Microsoft SQL and CSS developers curious about web development Anyone who wants to generate new income streams Anyone who wants to build dynamic web applications Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Anyone who wants to become a Full stack web developer Anyone who wants to build fully functional asp .net core mvc database applications

This is an accredited course with the International practitioners of Holistic medicine for women personally or professionally to transform their life. Relax, be calm, you've got this!

Duration 3 Days 18 CPD hours This course is intended for Students receive comprehensive Microsoft Dynamics exam preparation, becoming familiarized with the Dynamics CRM customization and configuration tools. Aspirants also learn to leverage the platform tools to create custom objects, automate tasks, modify user interface, and perform other such customizations. Overview Configure the Dynamics CRM settingsConfigure different entities and fieldsImplement entity relationships, custom actions, workflows, and dialogsIdentify scenarios for utilizing multiple forms, and design considerations for chartsSet default share views and public views, and configure and manage dashboardsIdentify role-based business processesIdentify and manage business requirements and teams This course explains everything you need to know about customizing and configuring the Dynamics CRM 365 system in accordance with a company?s specific requirements. Introduction to Customization and Configuring Dynamics CRM Talent and Course Introduction Module Overview CRM Overview What is Dynamics Customization and Configuration? CRM Architecture Customization Methodology Module review Obtaining a Dynamics CRM Trial TEST YOUR KNOWLEDGE MODULE 1' Manage Microsoft Dynamics CRM Online Subscriptions Module Overview Configuring CRM Overview of CRM Security User Administration Mailboxes Teams CRM Security Model Module Overview Purpose of the CCRM Security Model Privileges Access Levels Security Roles Hierarchy Security Hierarchy Types Module review Introduction to Solutions Module Overview Solutions Overview Solution Detail Creating and Working with Solutions Working with Solution Assets Exporting Solutions Importing Solutions Module review Entity and Field Customization Module Overview Types Entities Entity Ownership Entity Properties System vs Custom Entities Custom Entities and Security Roles Overview of Fields Field Properties Module review Additional Field Customization Module Overview Creating Fields to Meet Client Needs Calculated Fields Rollup Fields CRM Option Sets Alternate Keys Field Level Security State and Status Reason Transitions Module Review Configure mobile devices Module Overview Types of Relationships How and where they are created Many to Many Relationships Hierarchical Data Entity Mapping Connection and Connection Roles Module Review Customizing Forms Module Overview Form types Qualities of a good form Building a Form Specialized Form Components Access Teams and Sub Grids Working with Navigation Additional Form Types Multiple Forms Form customizations and Mobile Clients Module Review Business Rules Module Overview Business Rules Business Rule Scope Trigger Rules Condition and Actions Else Conditions and Actions Occur When Conditions Are True Module review Views and Visualizations Module Overview Using Views View Customization System View Types Quick Find Customization Charts Customizing Dashboard Themes Module Review Introduction to Processes Module Overview Processes and Automation Workflow Basics Module review Business Process Flows What are CRM Business Process Flows Enabling Business Process Flows Steps Stages and Categories Conditional Branching Module Review Bringing it all Together Module Overview Review of Customization Topics Covered Senario Packaging in a Solution Module review

Duration 3 Days 18 CPD hours This course is intended for Incoming attendees are required to have current, hands-on experience in developing basic web applications. Student should have some experience with HTML and CSS and be well versed in JavaScript. Experience with coding for the server side would be helpful. Overview This skills-focused course is approximately 50% hands-on. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Learn server-side JavaScript coding through Node.js Explore the latest JavaScript features, and ECMAScript modules Walk through different stages of developing robust applications using Node.js Install and use Node.js for development Use the Express application framework Work with REST service development using the Restify framework Use data storage engines such as MySQL, SQLITE3, and MongoDB Node.js is a server-side JavaScript platform using an event-driven, non-blocking I/O model allowing users to build fast and scalable data-intensive applications running in real time.This fast-paced hands-on course provides the core skills required to develop web applications with Node.js. You will progress from a rudimentary knowledge of JavaScript and server-side development to being able to create, maintain and test your own Node.js applications. You will explore the importance of transitioning to functions that return Promise objects, and the difference between fs, fs/promises and fs-extra, as well as how to use the HTTP Server and Client objects, and data storage with both SQL and MongoDB databases. Overview of Node.js The capabilities of Node.js Why should you use Node.js? The Node.js event-driven architecture Embracing advances in the JavaScript language Developing microservices or maxiservices with Node.js Setting Up Node.js System requirements Installing Node.js using package managers Installing from the source on POSIX-like systems Installing multiple Node.js instances with nvm Requirements for installing native code modules Choosing Node.js versions to use and the version policy Choosing editors and debuggers for Node.js Running and testing commands Advancing Node.js with ECMAScript 2015, 2016, 2017, and beyond Using Babel to use experimental JavaScript features Exploring Node.js Modules Defining a Node.js module Finding and loading modules using require and import Using npm ? the Node.js package management system The Yarn package management system HTTP Servers and Clients Sending and receiving events with EventEmitter Understanding HTTP server applications HTTP Sniffer ? listening to the HTTP conversation Web application frameworks Getting started with Express Creating an Express application to compute Fibonacci numbers Making HTTPClient requests Calling a REST backend service from an Express application Your First Express Application Exploring Promises and async functions in Express router functions Architecting an Express application in the MVC paradigm Creating the Notes application Theming your Express application Scaling up ? running multiple Notes instances Implementing the Mobile-First Paradigm Understanding the problem ? the Notes app isn't mobile friendly Learning the mobile-first paradigm theory Using Twitter Bootstrap on the Notes application Flexbox and CSS Grids Mobile-first design for the Notes application Using third-party custom Bootstrap themes Data Storage and Retrieval Remembering that data storage requires asynchronous code Logging and capturing uncaught errors Storing notes in a filesystem Storing notes with the LevelDB datastore Storing notes in SQL with SQLite3 Storing notes the ORM way with Sequelize Storing notes in MongoDB Additional course details: Nexus Humans Introduction to Node.js (TT4153) 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 Introduction to Node.js (TT4153) 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.

Duration 3 Days 18 CPD hours This course is intended for This introductory-level course is for experienced DBAs who will be working with MongoDB. In order to gain the most from this course you should have: Prior practical experience in Database Administration Experience working with Linux and be comfortable working with command line Overview This skills-focused course is approximately 50% hands-on. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will explore: The MongoDB Basic Architecture and Installation MongoDB administration User Management MongoDB security Indexes Backup & Recovery High Availability / Replication Diagnostics & Troubleshooting MongoDB is fast becoming the database of choice for big data applications, being one of the most popular and widely implemented NoSQL databases. Its scalability, robustness, and flexibility have made it extremely popular among business enterprises who use it to implement a variety of activities including social communications, analytics, content management, archiving and other activities. This has led to an increased demand for MongoDB administrators who have the skills to handle cross functional duties. Geared for experienced DBAs, MongoDB for DBAs is a three-day hands-on course that explores the concepts, architecture and pitfalls of managing a MongoDB installation. This course is targeted to the DBA who is familiar with the concepts and tasks of working with a Relational database and is not responsible for a NoSQL MongoDB database. You will learn the critical aspects of MongoDB and use it to solve data management challenges. You will learn to manage MongoDB effectively by gaining expertise in MongoDB administration tools, syntax, MongoDB installations, configurations, security, troubleshooting, backup, scaling and many other features. The focus of this course is on practical skills and applying the DBA existing database knowledge to a MongoDB installation. Introduction to MongoDB Basic Architecture and Installation Differentiate database categories Learn MongoDB design goals List MongoDB tools Describe JSON and BSON Understanding the basic concepts of a Database Database categories: What is NoSQL? Why NoSQL? Benefit over RDBMS Types of NoSQL Database, and NoSQL vs. SQL Comparison, ACID & Base Property CAP Theorem, implementing NoSQL and what is MongoDB? Graph Database Overview of MongoDB, Design Goals for MongoDB Server and Database, MongoDB tools Understanding the following: Collection, Documents and Key/Values, etc., Introduction to JSON and BSON documents Environment setup (live Handson) and using various MongoDB tools available in the MongoDB Package MongoDB Administration Take database backup and restore MongoDB© Export and import data from/ to a MongoDB© instance Check server status and DB status Monitor various resource utilization of a mongod instance Understand various optimization strategies Administration concepts in MongoDB Monitoring issues related to Database Monitoring at Server, Database, Collection level, and various Monitoring tools related to MongoDB Database Profiling, Locks, Memory Usage, No of connections, page fault etc., Backup and Recovery Methods for MongoDB Export and Import of Data to and from MongoDB Run time configuration of MongoDB Production notes/ best practices Data Managements in MongoDB (Capped Collections/ Expired data from TTL), TTL Collection Features GridFS Memory-Mapped Files Journaling Mechanics Storage Engines Power of 2-Sized Allocations No Padding Allocation Strategy Diagnosing Performance Issues Optimization Strategies for MongoDB Configure Tag Sets for Replica Set. Optimize Query Performance Monitoring Strategies for MongoDB . MongoDB Utilities MongoDB Commands MongoDB Management Service (MMS) Data Backup Strategies in MongoDB Copying Underlying Data Files Backup with MongoDump Fsync and Lock MongoDB Ops Manager Backup Software Security Strategies in MongoDB Authentication Implementation in MongoDB . Authentication in a Replica set Authentication on Sharded Clusters Authorization End-to-End Auditing for Compliance User Management Create a User Administrator. Add a User to a Database. Create/Assign User a Role. Verify/Modify a User Access/Privileges. Change a User?s Password MongoDB Security Knowing security concepts in MongoDB Understand how Authentication and Authorisation works Security Introduction Security Concepts Indexes Index Introduction, Index Concepts, Index Types Index Properties Index Creation and Indexing Reference Introduction to Aggregation Aggregation Approach to Aggregation sort Order Pipeline Operators and Indexes Text Indexes Aggregate Pipeline Stages Text Search MapReduce Index Creation Aggregation Operations Index Creation on Replica Set Remove, Modify, and Rebuild Indexes Listing Indexes Measure Index Use Control Index Use Index Use Reporting Geospatial Indexes MongoDB?s Geospatial Query Operators GeoWith Operator Backup & Recovery Import and Export MongoDB Data Restore and recovery of MongoDB(Including point in time Recovery) Restore a Replica Set from MongoDB Backups Recover Data after an Unexpected Shutdown Backup and Restore with Filesystem Snapshots Back Up and Restore with MongoDB Tools Backup and Restore Sharded Clusters High Availability (Replication ) Understand the concept of Replication in MongoDB© ? Create a production like Replica Set Introduction to Replication (High Availability), Concepts around Replication What is Replica Set and Master Slave Replication? Type of Replication in MongoDB How to setup a replicated cluster & managing replica sets etc., Master-Slave Replication Replica Set in MongoDB Automatic Failover Replica Set Members Write Concern Write Concern Levels Write Concern for a Replica Set Modify Default Write Concern Read Preference Read Preference Modes Blocking for Replication Tag Set Configure Tag Sets for Replica set. Replica Set Deployment Strategies . Replica Set Deployment Patterns Oplog File Replication State and Local Database, Replication Administration Diagnostics & Troubleshooting Troubleshoot slow queries Diagnose connectivity problems Understand diagnostic tools Learn common production issues Learn fixes and solutions. Additional course details: Nexus Humans Introduction to MongoDB for DBAs (TTDB4680) 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 Introduction to MongoDB for DBAs (TTDB4680) 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.