10117 Environment courses delivered On Demand

Highlights of the Course Course Type: Online Learning Duration: 4 Hours 18 Minutes Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about counselling and psychotherapy Understand the core competencies and principles of counselling and psychotherapy Explore the various areas of counselling and psychotherapy Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert counsellor and psychotherapist Psychotherapy Diploma Course Master the skills you need to propel your career forward in counselling and psychotherapy. This course will equip you with the essential knowledge and skillset that will make you a confident counsellor or psychotherapist and take your career to the next level. This comprehensive psychotherapy course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this psychotherapy course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective counselling and psychotherapy practice and equip you with the essential skills, confidence and competence to assist you in the counselling and psychotherapy industry. You'll gain a solid understanding of the core competencies required to drive a successful career in counselling and psychotherapy. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for counsellor or psychotherapist or for people who are aspiring to specialise in counselling and psychotherapy. Enrol in this psychotherapy course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive psychotherapy course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this counselling and psychotherapy can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This psychotherapy course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This psychotherapy course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This psychotherapy course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Introduction to the Course About the Instructor 00:04:00 About the Course 00:04:00 Introduction to Psychotherapy What is 'Psychotherapy'? 00:09:00 Difference between 'Counselling' and 'Psychotherapy' 00:10:00 Who needs psychotherapy? 00:08:00 Therapeutic Relationship & Environment Setting up therapeutic environment 00:08:00 Listening Skills & Listening Stages 00:09:00 Establishing positive therapeutic relationship 00:09:00 Stress - and Anger management 00:13:00 Approaches & Schools of Thought Person-Centred Therapy 00:09:00 Psychodynamic Therapy & Psychoanalysis 00:11:00 Gestalt Therapy 00:13:00 Existential Psychotherapy 00:08:00 Types & Forms of psychotherapy Individual Psychotherapy 00:06:00 Group sessions (workshops) 00:10:00 Couple psychotherapy 00:10:00 Online (Skype) Therapy 00:09:00 Mental Health Conditions Psychotherapy for Depression 00:08:00 Psychotherapy for Anxiety disorders 00:06:00 Psychotherapy for Schizophrenia 00:09:00 Gender Identity Disorder (Gender Dysphoria) 00:10:00 Psychotherapy for Eating Disorders 00:09:00 Helping the client in crisis Suicidal thinking & talking 00:09:00 Self harm cases 00:09:00 Relationship breakdown 00:09:00 Working as a Therapist How to set up own practice 00:08:00 Registration & Accreditation 00:08:00 Where to advertise own services 00:10:00 Thank you & Good Bye! 00:02:00 Assessment Assessment - Psychotherapy Diploma 00:10:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

The Bash Scripting, Linux and Shell Programming Masterclass course is a comprehensive guide to mastering Bash scripting, Linux, and shell programming. It's designed to address a common challenge: the complexity of navigating and controlling Linux-based systems. By simplifying these concepts, the course empowers learners to manage and operate within a Linux environment efficiently. The ability to script and program in the shell opens doors to streamlined processes, automation, and enhanced productivity, benefits that are crucial in today's tech-driven world. Through this masterclass, you will learn the essentials of Linux navigation, file management, and shell programming. Each section is crafted to build your skills progressively, ensuring a deep understanding of each aspect. Whether managing users, handling text files, or exploring advanced Bash features, the course is structured to provide practical, real-world applications. This approach not only enhances your technical skills but also boosts your problem-solving abilities within a Linux context. By the end of this course, you will be proficient in the technical aspects of Linux and Bash scripting and gain a strategic edge in applying these skills. The course is designed for accessibility, allowing learners to study at their own pace, from any device. This flexibility ensures that you can integrate learning seamlessly into your schedule, making it ideal for both beginners and those looking to refresh their skills Learning Outcomes Gain proficiency in basic Bash scripting and shell programming. Learn to navigate efficiently within the Linux environment. Develop skills to access and use help resources in Linux. Acquire expertise in managing files and folders in Linux. Understand how to manipulate and process text files. Learn to manage user accounts and permissions in Linux. Master techniques for terminating programs and safe logouts. Discover efficient shortcuts for faster Linux operations. Deepen understanding of Bash specifics and advanced features. Access a wealth of resources for ongoing Linux learning. Why choose this Bash Scripting, Linux and Shell Programming Masterclass? 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 Bash Scripting, Linux and Shell Programming Masterclass for? Beginners eager to learn about Linux and shell programming. IT professionals seeking to enhance their scripting skills. System administrators aiming to improve their Linux proficiency. Developers interested in automating tasks with Bash scripting. Anyone curious about mastering Linux-based systems. Career path Linux System Administrator: £25,000 - £50,000. DevOps Engineer: £30,000 - £70,000. IT Support Specialist: £20,000 - £40,000. Software Developer (with Linux skills): £25,000 - £55,000. Network Engineer: £25,000 - £50,000 Prerequisites This Bash Scripting, Linux and Shell Programming Masterclass does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Bash Scripting, Linux and Shell Programming Masterclass 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 Section 01: Introduction Introduction 00:02:00 Bash vs Shell vs Command Line vs Terminal 00:06:00 Section 02: Navigation Listing Folder Contents (ls) 00:05:00 Print Current Folder (pwd) 00:01:00 Change Folder (cd) 00:03:00 Using A Stack To Push Folders (pushd/popd) 00:03:00 Check File Type (file) 00:01:00 Find File By Name (locate) & Update Locate Database (updatedb) 00:02:00 Find A Command (which) 00:02:00 Show Command History (history) 00:02:00 Section 03: Getting Help Show Manual Descriptions (whatis) 00:01:00 Search Manual (apropos) 00:02:00 Reference Manuals (man) 00:02:00 Section 04: Working With Files/Folders Creating A Folder (mkdir) 00:02:00 Creating A File (touch) 00:02:00 Copy Files/Folders (cp) 00:02:00 Move & Rename Files/Folders (mv) 00:02:00 Delete Files/Folders (rm) 00:02:00 Delete Empty Folder (rmdir) 00:02:00 Change File Permissions (chmod) 00:06:00 Section 05: Text Files File Concatenation (cat) 00:03:00 File Perusal Filter (more/less) 00:02:00 Terminal Based Text Editor (nano) 00:03:00 Section 06: Users Run Commands As A Superuser (sudo) 00:03:00 Change User (su) 00:03:00 Show Effecter User and Group IDs (id) 00:02:00 Section 07: Killing Programs & Logging Out Kill A Running Command (ctrl + c) 00:02:00 Kill All Processes By A Name (killall) 00:02:00 Logging Out Of Bash (exit) 00:01:00 Section 08: Shortcuts Tell Bash That There Is No More Input (ctrl + d) 00:02:00 Clear The Screen (ctr + l) 00:02:00 Zoom In (ctrl + +) 00:02:00 Zoom Out (ctrl + -) 00:02:00 Moving The Cursor 00:02:00 Deleting Text 00:04:00 Fixing Typos 00:03:00 Cutting and Pasting 00:03:00 Character Capitalisation 00:03:00 Section 09: Bash Bash File Structure 00:03:00 Echo Command 00:04:00 Comments 00:04:00 Variables 00:06:00 Strings 00:06:00 While Loop 00:04:00 For Loop 00:04:00 Until Loop 00:03:00 Break & Continue 00:03:00 Get User Input 00:02:00 If Statement 00:09:00 Case Statements 00:06:00 Get Arguments From The Command Line 00:04:00 Functions 00:05:00 Global vs Local Variables 00:03:00 Arrays 00:06:00 Shell & Environment Variables 00:06:00 Scheduled Automation 00:03:00 Aliases 00:03:00 Wildcards 00:03:00 Multiple Commands 00:02:00 Section 10: Resource Resource 00:00:00 Assignment Assignment - Bash Scripting; Linux and Shell Programming Masterclass 00:00:00

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

This course will provide you with practical experience in C++. You will learn the basics and advanced concepts of C++, such as data types, arrays, functions, encapsulation, inheritance, exception handling, object-oriented programming (OOP), and a lot more, by developing interesting real-world applications.

Dealing with the challenges of Volatility, Uncertainty, complexity and Ambiguity

Explore the fascinating world of feline behavior and psychology with our comprehensive course, 'Feline Behaviour and Psychology: Understanding Cats.' Uncover the secrets behind your cat's actions, learn effective training techniques, and gain insights into promoting their overall well-being. From daily activities to emergencies, this course equips you with the knowledge to forge a stronger bond with your feline companion. Join us on this educational journey and unravel the mysteries of your cat's mind. Enroll now for a purr-fectly enriching experience!

Gain comprehensive skills in elderly care with our 4-in-1 Certificate in Elderly Care bundle. Learn about ageing, safeguarding, end-of-life care, and more. Start your rewarding career today!

Complete your first aid training with our comprehensive course covering First Aid at Work, Paediatric First Aid, Sports First Aid, and Mental Health First Aid. Ideal for workplace safety officers, childcare providers, sports coaches, and anyone looking to enhance their emergency response skills.

Illuminating the Hidden - Design for Sustainability as a Path Toward More Sustainable Products, More Sustainable Thinking, More Sustainable Corporate Cultures Consumers and other purchasers understand now more than ever that there are hidden impacts in the products and services they purchase. Leading companies now realize that they need to incorporate sustainability into their product development processes. To do that, they need product development teams who know how to 'think' in terms of sustainability, and fostering such thinking requires shifts bigger than the single product on the shelf - it's about transforming corporate culture. This session will walk through the concepts behind Design for Sustainability. It will highlight as a case study a collaborative partnership between UL Environment and Ingersoll Rand in fostering sustainability thinking in Ingersoll Rand through its product development process. The session will end with a brief overview of steps that companies can take to start incorporating design for sustainability thinking in their organizations. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies.

The Power of Vision in the Digital Age What's the secret behind running a successful project? Everyone is looking for the magic bullet, the secret sauce, or the universal solution. It's not just a matter of having the right people on the project, it's also knowing what the vision is and what the purpose behind the vision is. But there is more to it. And what are the challenges and opportunities with running a successful project in the digital age? During this session, we elaborate on this and give you some tips to apply this to your project environment as well. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.