388 Courses in Cardiff delivered On Demand

🚀 Supercharge Your Product Development Process with the Rapid Product Development Workshop! 🚀   Are you tired of lengthy product development cycles that drain your resources and hinder your innovation? Ready to streamline your process and bring your ideas to life faster than ever? Look no further than our exclusive Rapid Product Development Workshop!   🌟 What You'll Gain: 🔹 Proven Strategies: Learn battle-tested methodologies to accelerate product development without compromising quality. 🔹 Hands-On Techniques: Dive into practical exercises and real-world case studies that reinforce your learning experience. 🔹 Expert Guidance: Access to industry experts who will guide you through each step, providing invaluable insights and personalized feedback. 🔹 Time-Saving Tools: Discover a toolkit of resources designed to optimize your workflow and maximize efficiency.   🔥 Key Workshop Features: ✅ Module 1: Understanding Rapid Product Development Fundamentals ✅ Module 2: Ideation and Concept Validation Techniques ✅ Module 3: Rapid Prototyping and Iterative Design Methods ✅ Module 4: Agile Development Principles for Speed and Flexibility ✅ Module 5: Testing, Feedback, and Rapid Refinement Strategies   🎯 Who Is This For: 🚀 Entrepreneurs aiming to launch products swiftly and gain a competitive edge. 🔬 Innovators looking to revolutionize their approach to product development. 📈 Teams seeking to optimize their workflow for faster, more efficient outcomes.   📅 Workshop Details: 📍 Online Sessions: Attend from anywhere in the world, at your own pace. 🗓️ Flexible Schedule: Choose sessions that fit your timetable - no need to disrupt your daily routine. 📜 Certificate of Completion: Earn recognition for enhancing your skills and mastering rapid product development strategies.   🌟 Limited-Time Offer: Enroll now and unlock the secrets to rapid product development at an exclusive discounted rate! Don't miss this chance to revolutionize your approach and fast-track your success! Join the Rapid Product Development Workshop today and propel your ideas from concept to reality at lightning speed! 💡💫 Course Curriculum

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

Explore the intricacies of Dialectical Behaviour Therapy (DBT) in our comprehensive course. From foundational principles to practical applications, gain expertise in mindfulness, emotion regulation, interpersonal effectiveness, and distress tolerance skills. Learn to implement DBT ethically in diverse clinical settings and with specific populations. Elevate your therapeutic practice with evidence-based strategies. Join us for a transformative learning experience.

Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

This course covers all the basics to more advanced features and dives into all the little details about Hasura. Hasura provides a platform to create your GraphQL backends easier and faster than you ever thought possible without writing a single line of code!

Microsoft Excel 2016 Advanced is one of our best selling and most popular course. This course is suitable for anyone aspiring to or already working in Microsoft Excel and looks at skills needed to improve Microsoft Excel. By taking this course you will gain the necessary skills to perform effectively in this field. The Microsoft Excel 2016 Advanced is organised into 6 modules and includes everything you need to become successful in this profession. To make this course more accessible for you, we have designed it for both part-time and full-time students. You can study at your own pace or become an expert in just 8hours! If you require support, our experienced tutors are always available to help you throughout the comprehensive syllabus of this course and answer all your queries through email. Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification 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. Course Content Automating Worksheet Functionality Update Workbook Properties 00:15:00 Activity-Update Workbook Properties 00:05:00 Create and Edit a Macro 00:15:00 Activity-Create and Edit a Macro 00:05:00 Apply Conditional Formatting 00:30:00 Activity-Apply Conditional Formatting 00:05:00 Add Data Validation Criteria 00:15:00 Activity-Add Data Validation Criteriaty 00:05:00 Auditing Worksheets Trace Cells 00:15:00 Activity-Trace Cells 00:05:00 Troubleshoot Invalid Data and Formula Errors 00:15:00 Activity-Troubleshoot Invalid Data and Formula Errors 00:05:00 Watch and Evaluate Formulas 00:15:00 Activity-Watch and Evaluate Formulas 00:05:00 Create a Data List Outline 00:15:00 Activity-Create a Data List Outline 00:05:00 Analyzing and Presenting Data Create Sparklines 00:15:00 Activity_Create Sparklines 00:05:00 Create Scenarios 00:15:00 Activity-Create Scenarios 00:05:00 Perform a What-If Analysis 00:15:00 Activity-Perform a What-If Analysis 00:05:00 Perform a Statistical Analysis with the Analysis ToolPak 00:15:00 Activity-Perform a Statistical Analysis with the Analysis ToolPak 00:05:00 Create Interactive Data with Power View 00:15:00 Activity-Create Interactive Data with Power View 00:05:00 Working with Multiple Workbooks Consolidate Data 00:15:00 Activity-Consolidate Data 00:05:00 Link Cells in Different Workbooks 00:15:00 Activity-Link Cells in Different Workbooks 00:05:00 Merge Workbooks 00:15:00 Activity-Merge Workbooks 00:05:00 Exporting Excel Data Export Excel Data 00:15:00 Activity-Export Excel Data 00:05:00 Import a Delimited Text File 00:14:00 Activity- Import a Delimited Text File 00:05:00 Integrate Excel Data with the Web 00:15:00 Activity-Integrate Excel Data with the Web 00:05:00 Create a Web Query 00:15:00 Activity-Create a Web Query 00:05:00 Importing and Exporting XML Data Import and Export XML Data 00:15:00 Activity-Import and Export XML Data 00:05:00 Activities Activities and Exercise Files - Microsoft Excel 2016 Advanced 00:00:00 Mock Exam Mock Exam- Microsoft Excel 2016 Advanced 00:20:00 Final Exam Final Exam- Microsoft Excel 2016 Advanced 00:20:00 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.

This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

Duco Digital Training's course in BCS Requirements Engineering Practitioner develops your skills in the understanding and application of elicitation, analysis and management of business analysis requirements.

FREE Certification: QLS Endorsed + CPD Accredited | Instant Access | Round-the-Clock Tutor Support | All-Inclusive Cost

Description: Nowadays almost every job in the business world involves office products. Whether you're an administrative assistant, office manager, sales professional or business manager, utilizing all of the powerful features of Microsoft Office will make you more efficient and subsequently more marketable. The Microsoft Office 2016 Access Complete Video Course - Beginner, Intermediate & Advanced is designed to provide you all the basics of relational database design and through the creation of database objects. You will learn how to use forms, query tables and reports to manage data. You will understand the interface, customization and creation editing of the many objects available within the Microsoft Access application. This course is divided into three separate levels being Basic Microsoft Access, Intermediate Microsoft Access and Advanced Microsoft Access. Assessment: At the end of the course, you will be required to sit for an online MCQ test. Your test will be assessed automatically and immediately. You will instantly know whether you have been successful or not. 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. Who is this Course for? Microsoft Office 2016 Access Complete Video Course - Beginner, Intermediate & Advanced is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Microsoft Office 2016 Access Complete Video Course - Beginner, Intermediate & Advanced is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. 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. Microsoft Access - Beginner Orientation to Microsoft Access FREE 00:39:00 Create a Simple Access Database 00:10:00 Get Help and Configure Options in Microsoft Access 00:06:00 Modify Table Data 00:17:00 Sort and Filter Records 00:05:00 Create Basic Queries 00:15:00 Sort and Filter Data in a Query 00:14:00 Perform Calculations in a Query 00:08:00 Create Basic Access Forms 00:07:00 Work with Data on Access Forms 00:23:00 Create a Report 00:23:00 Add Controls to a Report 00:12:00 Enhance the Appearance of a Report 00:05:00 Prepare a Report for Print 00:03:00 Organize Report Information 00:15:00 Format Reports 00:12:00 Microsoft Access - Intermediate Relational Database Design FREE 00:16:00 Create a Table 00:09:00 Create Table Relationships 00:09:00 Create Query Joins 00:14:00 Relate Data Within a Table.avi 00:04:00 Work with Subdatasheets from 00:05:00 Use Field Validation 00:16:00 Use Form and Record Validation 00:14:00 Create Parameter Queries 00:12:00 Summarize Data 00:06:00 Create Subqueries 00:07:00 Create Action Queries 00:05:00 Create Unmatched and Duplicate Queries 00:06:00 Data Normalization 00:10:00 Create a Junction Table 00:04:00 Improve Table Structure 00:06:00 Include Control Formatting in a Report 00:04:00 Add a Calculated Field to a Report 00:05:00 Add a Subreport to an Existing Report 00:07:00 Microsoft Access - Advanced Add Controls to Forms FREE 00:11:00 Enhance Navigation and Organization of Forms 00:14:00 Apply Conditional Formatting 00:04:00 Import Data into Access 00:08:00 Export Access Data 00:06:00 Link Tables to External Data Sources 00:05:00 Create a Mail Merge 00:02:00 Create a Macro 00:08:00 Restrict Records by Using a Condition 00:04:00 Validate Data by Using a Macro 00:05:00 Automate Data Entry by Using a Macro 00:04:00 Manage a Database 00:08:00 Determine Object Dependency 00:04:00 Manage a Database 00:07:00 Determine Object Dependency 00:04:00 Document a Database 00:04:00 Splitting a Database for Multiple User Access 00:05:00 Implement Security 00:03:00 Convert an Access Database to an ACCDE File 00:04:00 Package a Database with a Digital Signature 00:01:00 Create a Database Switchboard 00:05:00 Modify a Database Switchboard 00:02:00 Set Start up Options 00:04:00 Mock Exam Mock Exam- Microsoft Office 2016 Access Complete Video Course - Beginner, Intermediate & Advanced 00:30:00 Final Exam Final Exam- Microsoft Office 2016 Access Complete Video Course - Beginner, Intermediate & Advanced 00:30:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00