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This Design Patterns course is a unique offering that focuses on modern C++ features and behavioral design patterns. The course content is extensive and carefully curated, with a deep dive into each pattern to ensure a thorough understanding of its implementation. Gain a comprehensive understanding of the pattern's intricacies.

Overview This comprehensive course on Clinical Data Analysis with SAS will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Clinical Data Analysis with SAS 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 Clinical Data Analysis with SAS. It is available to all students, of all academic backgrounds. Requirements Our Clinical Data Analysis with SAS 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 5 sections • 30 lectures • 01:54:00 total length •Course Promo: 00:01:00 •1.1 Components of the Pharma Industry: 00:05:00 •1.2 Phases of Clinical Trials: 00:06:00 •1.3 Data and Reports in Clinical Trials: 00:04:00 •1.4 Types of Data: 00:05:00 •2.1 Clinical Study Protocol: 00:02:00 •2.2 Ethical Consent: 00:01:00 •2.3 Inclusion-Exclusion Criteria: 00:01:00 •2.4 Statistical Analysis Plan: SAP, Mockshell and CRF: 00:04:00 •3.1 General SAS Programming Steps: 00:02:00 •3.2 One Search Report: Demographics Table: 00:04:00 •3.3 Understanding the Demographics Table: 00:03:00 •3.4 Programming the Demographics Table: 00:05:00 •3.5 Importing Raw Demographic Data into the SAS: 00:04:00 •3.6 Deciding what Procedure to Use: 00:02:00 •3.7 Deriving the AGE variable: 00:10:00 •3.8 Obtaining Summary Statistics for AGE: 00:04:00 •3.9 Adding the 3rd Treatment Group using Explicit Output: 00:05:00 •3.10 Deriving the SEX variable: 00:03:00 •3.11 Obtaining Summary Statistics for SEX: 00:03:00 •3.12 Concatenating the COUNT and PERCENT Variables: 00:03:00 •3.13 Deriving the RACE Variable: 00:03:00 •3.14 Obtaining Summary Statistics for RACE: 00:03:00 •3.15 Stacking All the 3 Summary Statistics Together: 00:06:00 •3.16 Fixing the Precision Points: 00:04:00 •3.17 Transposing Data: 00:03:00 •3.18 Fixing the Order of Statistical Parameters: 00:05:00 •3.19 Building the Final Report: 00:02:00 •3.20 Putting the Final Touches to the Report: 00:11:00 •Resources - Clinical Data Analysis with SAS: 00:00:00

A course that focuses on using Kotlin for server-side development using the Spring Boot framework. This hands-on course will help you get familiar with the basics of the Kotlin programming language as well as the entire process of building RESTful APIs using Kotlin Spring Boot.

Dive into the dynamic realm of clinical data analysis with our comprehensive Clinical Data Analysis with SAS course. This course is your passport to the pharmaceutical industry, guiding you through the essential components, phases of clinical trials, and types of data crucial in this field. You'll gain proficiency in interpreting clinical study documents, from protocols to ethical consent, enabling you to navigate the intricate world of clinical data. Our course equips you with SAS programming skills, empowering you to develop clinical study reports, analyze demographic data, and derive valuable insights. Whether you're a budding data analyst or a professional aiming to enhance your clinical data expertise, this course provides the knowledge and skills needed for a successful career in clinical data analysis. Learning Outcomes Understand the key components and phases of the pharmaceutical industry. Navigate clinical trials with insights into data types and reports. Interpret clinical study documents, including protocols and ethical consent. Develop clinical study reports using SAS programming. Analyze demographic data and derive valuable insights. Why choose this Clinical Data Analysis with SAS course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the 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. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Clinical Data Analysis with SAS course for? Aspiring clinical data analysts seeking to enter the pharmaceutical industry. Professionals in healthcare, research, or data analysis looking to enhance their clinical data expertise. Students and individuals interested in clinical data and its analysis. Those who want to decode clinical study documents and reports. Anyone aiming to unlock the world of clinical data analysis with SAS. Career path Clinical Data Analyst: £25,000 - £50,000 Biostatistician: £30,000 - £70,000 Pharmaceutical Researcher: £25,000 - £60,000 Data Scientist in Healthcare: £30,000 - £70,000 Clinical SAS Programmer: £28,000 - £60,000 Clinical Research Manager: £35,000 - £80,000 Prerequisites This Clinical Data Analysis with SAS does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Clinical Data Analysis with SAS 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. Course Curriculum Course Promo Course Promo 00:01:00 Section 01: Introduction 1.1 Components of the Pharma Industry 00:05:00 1.2 Phases of Clinical Trials 00:06:00 1.3 Data and Reports in Clinical Trials 00:04:00 1.4 Types of Data 00:05:00 Section 02: Knowledge on Clinical Study Documents 2.1 Clinical Study Protocol 00:02:00 2.2 Ethical Consent 00:01:00 2.3 Inclusion-Exclusion Criteria 00:01:00 2.4 Statistical Analysis Plan: SAP, Mockshell and CRF 00:04:00 Section 03: Developing the Clinical Study Reports 3.1 General SAS Programming Steps 00:02:00 3.2 One Search Report: Demographics Table 00:04:00 3.3 Understanding the Demographics Table 00:03:00 3.4 Programming the Demographics Table 00:05:00 3.5 Importing Raw Demographic Data into the SAS 00:04:00 3.6 Deciding what Procedure to Use 00:02:00 3.7 Deriving the AGE variable 00:10:00 3.8 Obtaining Summary Statistics for AGE 00:04:00 3.9 Adding the 3rd Treatment Group using Explicit Output 00:05:00 3.10 Deriving the SEX variable 00:03:00 3.11 Obtaining Summary Statistics for SEX 00:03:00 3.12 Concatenating the COUNT and PERCENT Variables 00:03:00 3.13 Deriving the RACE Variable 00:03:00 3.14 Obtaining Summary Statistics for RACE 00:03:00 3.15 Stacking All the 3 Summary Statistics Together 00:06:00 3.16 Fixing the Precision Points 00:04:00 3.17 Transposing Data 00:03:00 3.18 Fixing the Order of Statistical Parameters 00:05:00 3.19 Building the Final Report 00:02:00 3.20 Putting the Final Touches to the Report 00:11:00 Resources Resources - Clinical Data Analysis with SAS 00:00:00 Assignment Assignment - Clinical Data Analysis with SAS 00:00:00

In this competitive job market, you need to have some specific skills and knowledge to start your career and establish your position. This Xero Australia - Accounting & Bookkeeping will help you understand the current demands, trends and skills in the sector. The course will provide you with the essential skills you need to boost your career growth in no time. The Xero Australia - Accounting & Bookkeeping will give you clear insight and understanding about your roles and responsibilities, job perspective and future opportunities in this field. You will be familiarised with various actionable techniques, career mindset, regulations and how to work efficiently. This course is designed to provide an introduction to Xero Australia - Accounting & Bookkeeping and offers an excellent way to gain the vital skills and confidence to work toward a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Learning Objectives Learn the fundamental skills you require to be an expert Explore different techniques used by professionals Find out the relevant job skills & knowledge to excel in this profession Get a clear understanding of the job market and current demand Update your skills and fill any knowledge gap to compete in the relevant industry CPD accreditation for proof of acquired skills and knowledge Who is this Course for? Whether you are a beginner or an existing practitioner, our CPD accredited Xero Australia - Accounting & Bookkeeping is perfect for you to gain extensive knowledge about different aspects of the relevant industry to hone your skill further. It is also great for working professionals who have acquired practical experience but require theoretical knowledge with a credential to support their skill, as we offer CPD accredited certification to boost up your resume and promotion prospects. Entry Requirement Anyone interested in learning more about this subject should take this Xero Australia - Accounting & Bookkeeping. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. The course is open to students from any academic background, as there is no prerequisites to enrol on this course. The course materials are accessible from an internet enabled device at anytime of the day. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £9 and the hard copy for £15. Also, you can order both PDF and hardcopy certificates for £22. Career path The Xero Australia - Accounting & Bookkeeping will help you to enhance your knowledge and skill in this sector. After accomplishing this course, you will enrich and improve yourself and brighten up your career in the relevant job market. Course Curriculum Section 01: Introduction Introduction 00:03:00 Section 02: Getting Started Introduction - Getting Started 00:01:00 Signing up to Xero 00:04:00 Quick Tour of Xero 00:16:00 Initial Xero Settings 00:15:00 Chart of Accounts 00:16:00 Adding a Bank Account 00:07:00 Demo Company 00:04:00 Tracking Categories 00:07:00 Contacts 00:14:00 Section 03: Invoices and Sales Introduction - Invoices and Sales 00:01:00 Sales Screens 00:05:00 Invoice Settings 00:13:00 Creating an Invoice 00:21:00 Repeating Invoices 00:06:00 Credit Notes 00:10:00 Quotes Settings 00:03:00 Creating Quotes 00:07:00 Other Invoicing Tasks 00:04:00 Sending Statements 00:03:00 Sales Reporting 00:06:00 Section 04: Bills and Purchases Introduction - Bills and Purchases 00:01:00 Purchases Screens 00:06:00 Bill Settings 00:02:00 Creating a Bill 00:14:00 Repeating Bills 00:04:00 Credit Notes 00:05:00 Purchase Order Settings 00:01:00 Purchase Orders 00:07:00 Batch Payments 00:14:00 Other Billing Tasks 00:02:00 Sending Remittances 00:03:00 Purchases Reporting 00:05:00 Section 05: Bank Accounts Introduction - Bank Accounts 00:01:00 Bank Accounts Screens 00:08:00 Automatic Matching 00:05:00 Reconciling Invoices 00:07:00 Reconciling Bills 00:03:00 Reconciling Spend Money 00:05:00 Reconciling Receive Money 00:04:00 Find and Match 00:04:00 Bank Rules 00:12:00 Cash Coding 00:03:00 Remove and Redo vs Unreconcile 00:04:00 Uploading Bank Transactions 00:07:00 Automatic Bank Feeds 00:05:00 Section 06: Products and Services Introduction - Products and Services 00:01:00 Products and Services Screen 00:02:00 Adding Services 00:04:00 Adding Untracked Products 00:03:00 Adding Tracked Products 00:07:00 Section 07: Fixed Assets Introduction - Fixed Assets 00:01:00 Fixed Assets Settings 00:05:00 Adding Assets from Bank Transactions 00:06:00 Adding Assets from Spend Money 00:04:00 Adding Assets from Bills 00:01:00 Depreciation 00:04:00 Section 08: Basic Payroll Introduction - Payroll 00:01:00 Payroll Settings 00:24:00 Adding Employees 00:32:00 My Payroll 00:06:00 Single Touch Payroll 00:04:00 Paying Employees 00:13:00 Section 09: Basic Activity Statements Introduction - Activity Statements 00:01:00 Activity Statement Settings 00:12:00 Lodging Activity Statements 00:06:00 Section 10: Conclusion What Now! 00:01:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the 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. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science 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. Course Curriculum Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

Learn Java programming step-by-step with 250 core features and 200+ code examples, perfect for absolute beginners. This hands-on course covers everything from basic concepts to advanced topics such as functional programming and exception handling using JShell and Eclipse as an IDE. Gain a solid foundation in Java and kickstart your programming career.

OCA Prep Included

In the complex realm of healthcare, where lives are entrusted to capable hands, lies the pivotal concept of Clinical Governance. Imagine a world where every medical decision is guided by a strong framework of quality, safety, and ethical standards. Welcome to the transformative course Clinical Governance, where you'll embark on a journey to master the art of effective healthcare management and ensure the delivery of exceptional patient care. Learning Outcome: At the end of this Clinical Governance course, learners are expected to - Develop a comprehensive understanding of Clinical Governance principles and practices. Gain knowledge of the 7 pillars that form the foundation of Clinical Governance. Understand the role of clinical effectiveness and audits in healthcare. Learn about confidentiality, information technology, legal aspects, and ethics in Clinical Governance. Acquire the skills to maintain workplace safety and adapt to healthcare challenges like COVID-19. Clinical Governance is more than just a buzzword - it is a fundamental approach that empowers healthcare professionals to continuously improve the quality and safety of patient care. Through a series of engaging modules, such as Introduction to Clinical Governance and The 7 Pillars of Clinical Governance, you'll gain a comprehensive understanding of the principles and practices that underpin this critical concept. From clinical effectiveness and audits to confidentiality and workplace safety, this Clinical Governance course covers a wide range of topics that are essential for healthcare professionals in today's ever-evolving medical landscape. Whether you're a healthcare professional seeking to enhance your knowledge and skills, a medical administrator responsible for ensuring the highest standards of care, or simply interested in understanding the inner workings of the healthcare system, the Clinical Governance course is designed for you. Join us on this transformative journey and become a champion of quality, safety, and excellence in healthcare. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Clinical Governance course is suitable for - Healthcare professionals seeking to enhance their knowledge and skills in healthcare management. Medical administrators responsible for ensuring quality, safety, and compliance in healthcare settings. Individuals interested in understanding the inner workings of the healthcare system and its governance. Career path Clinical Governance Manager: £40,000 - £60,000 per year Quality Improvement Officer: £35,000 - £50,000 per year Healthcare Compliance Specialist: £30,000 - £45,000 per year Healthcare Administrator: £25,000 - £40,000 per year Clinical Auditor: £30,000 - £50,000 per year

Learning Objectives Introduction , Interviewing Pitfalls , Before the Interview , During the Interview , After the Interview , Conclusion   Pre-Requisites There are no prerequisites for this course.   Description One of the most important decisions a company can make is hiring new employees. Good hiring decisions can make or break teams and can have a direct impact on a company's bottom line. Additionally, increasing diversity in hiring is about more than simple fair hiring practices. Research shows diverse teams make faster decisions and are more innovative. This class is designed to assist managers, supervisors, and HR staff in improving interviewing skills. Course Introduction Introduction 00:02:00 Section 01 Lesson 01: What is Unconscious Bias 00:05:00 Lesson 02: Overcoming Unconscious Bias 00:03:00 Section 02 Lesson 01: Creating the Job Description 00:03:00 Lesson 02: Planning the Questions 00:03:00 Lesson 03: Building a Scorecard 00:02:00 Lesson 04: Preparing for the Interview 00:02:00 Section 03 Lesson 01: Setting Candidates at Ease 00:01:00 Lesson 02: Conducting the Interview 00:03:00 Lesson 03: Selling the Job 00:02:00 Section 04 Lesson 01: Making the Big Decision 00:02:00 Course Recap Recap 00:01:00