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Start your career in Data Science and earn up to £90,000 per month. Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course. Our mission is simple - to be your trusted partner every step of the way, from training to employment. In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door. If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist! If you have any questions, you can contact us. We will be happy to provide you with all the information you need. Why Choose Us? So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python: Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python. One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise. Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere. Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress. Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us. Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. Here are the courses we will provide once you enrol in the program: Course 01: Business and Data Analytics for Beginners Course 02: Quick Data Science Approach from Scratch Course 03: Learn MySQL from Scratch for Data Science and Analytics Course 04: SQL for Data Science, Data Analytics and Data Visualization Course 05: Statistics & Probability for Data Science & Machine Learning Course 06: R Programming for Data Science Course 07: Python Data Science with Numpy, Pandas and Matplotlib Course 08: Complete Python Machine Learning & Data Science Fundamentals Course 09: 2021 Data Science & Machine Learning with R from A-Z Course 10: Python Programming from Scratch with My SQL Database Course 11: Level 2 Python Course Course 12: Machine Learning for Predictive Maps in Python and Leaflet Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI Course 14: Python for Spatial Analysis in ArcGIS Course 15: Ultimate Python Training for Beginners Course 16: PyScript Fundamentals Training How Can We Offer Job Guarantees? HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector. The Data Scientist with Python Program is completed in 9 easy steps: Step 1: Enrol in the Programme Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied. After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing! Step 2: Initial One-On-One Counselling Session Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path. Step 3 - Certification upon Course Completion After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject. Step 4: CV Revamping Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. Step 5: Building Network and Submitting CV We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile. Step 6: Interview Preparation With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills. Step 7: Securing Job Interviews Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want. Step 8: Post-Interview Support Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job. Step 9: Celebrate Your New Job! Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role. We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us. CPD 100 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Beginners with an interest in Data Science and Python programming. Programmers and Software Engineers looking to transition into Data Science. Business Analysts and Project Managers aiming to leverage Data Science in their domains. Researchers and Academics who wish to utilise Python for complex data analysis. Requirements No experience required. Just enrol & start learning. Career path Data Scientist: £60,000 - £90,000 Machine Learning Engineer: £65,000 - £100,000 Data Analyst: £40,000 - £60,000 Business Intelligence Analyst: £45,000 - £70,000 Data Engineer: £50,000 - £80,000 Big Data Architect: £70,000 - £120,000 Certificates CPD Accredited e-Certificate Digital certificate - Included CPD Accredited Framed (Hardcopy) Certificate Hard copy certificate - Included Enrolment Letter Digital certificate - Included QLS Endorsed Hard Copy Certificate Hard copy certificate - Included Student ID Card Digital certificate - Included

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

Conflict Resolution Skills: In-House Training Many organizations have assumed that workplace conflict is always destructive. So, they have often believed that conflict is best dealt with by managers or even via policies and procedures. After all, conflict creates workplace stress and leads to many performance problems, generating very real organizational costs! However, savvy organizations have embraced the fact that when conflict is understood and harnessed, it can be leveraged to add value to teams and even enhance performance. With the right knowledge, skills, training, and practice, conflict can be productive and make organizations better! In this highly interactive course, learners will discover the connection between individual conflict response and team-empowering conflict resolution skills. Participants will explore conflict's visceral dynamics and the nuanced behaviors we individually engage in to communicate and respond to conflict. Learners will apply techniques for transforming unproductive conflict responses into productive ones. Additionally, learners will use a systematic method that prepares them to objectively dissect real-world conflict, while practicing many strategies for resolving it. They will also develop proactive conflict approach plans, which they can transfer back to their own workplaces. What you will Learn At the end of this program, you will be able to: Recognize the organizational costs of conflict Explain our physical and mental responses to conflict Communicate proactively and effectively with different types of people during conflict Replace unproductive conflict responses with productive ones Use the Conflict Resolution Diagram (CRD) process and conflict resolution approaches Relate team stages of development to shifts in conflict Develop a proactive conflict approach for your organization Create a conflict resolution plan for a real-world scenario Getting Started Introductions and social agreements Course goal and objectives Opening activities Conflict Facilitation Readiness Conflict responses and perceptions Conflict basics Conflict and organizations Dynamics of conflict Conflict Styles and Communication A look at the color energies model Conflict through the color energies and DiSC® lens Communication with opposite color energies Individual Response to Conflict The anatomy of conflict Recognizing unproductive conflict responses 4 steps to productive conflict Choosing productive conflict responses Team Performance and Conflict High-performing team relationships Conflict and project team performance Conflict Resolution Diagram (CRD) and process Conflict Facilitation - Preparation Recognizing context and stakeholder needs Using team conflict resolution approaches Preparing for Crucial Conversations® Conflict Facilitation - Clarity Exposing assumptions and biases Defining the conflict and using the CRD Conflict Facilitation - Action Proactive conflict management Conflict facilitation practice Summary and Next Steps Review Personal action plans

Conflict Resolution Skills (In-Person) Many organizations have assumed that workplace conflict is always destructive. So, they have often believed that conflict is best dealt with by managers or even via policies and procedures. After all, conflict creates workplace stress and leads to many performance problems, generating very real organizational costs! However, savvy organizations have embraced the fact that when conflict is understood and harnessed, it can be leveraged to add value to teams and even enhance performance. With the right knowledge, skills, training, and practice, conflict can be productive and make organizations better! In this highly interactive course, learners will discover the connection between individual conflict response and team-empowering conflict resolution skills. Participants will explore conflict's visceral dynamics and the nuanced behaviors we individually engage in to communicate and respond to conflict. Learners will apply techniques for transforming unproductive conflict responses into productive ones. Additionally, learners will use a systematic method that prepares them to objectively dissect real-world conflict, while practicing many strategies for resolving it. They will also develop proactive conflict approach plans, which they can transfer back to their own workplaces. What you will Learn At the end of this program, you will be able to: Recognize the organizational costs of conflict Explain our physical and mental responses to conflict Communicate proactively and effectively with different types of people during conflict Replace unproductive conflict responses with productive ones Use the Conflict Resolution Diagram (CRD) process and conflict resolution approaches Relate team stages of development to shifts in conflict Develop a proactive conflict approach for your organization Create a conflict resolution plan for a real-world scenario Getting Started Introductions and social agreements Course goal and objectives Opening activities Conflict Facilitation Readiness Conflict responses and perceptions Conflict basics Conflict and organizations Dynamics of conflict Conflict Styles and Communication A look at the color energies model Conflict through the color energies and DiSC® lens Communication with opposite color energies Individual Response to Conflict The anatomy of conflict Recognizing unproductive conflict responses 4 steps to productive conflict Choosing productive conflict responses Team Performance and Conflict High-performing team relationships Conflict and project team performance Conflict Resolution Diagram (CRD) and process Conflict Facilitation - Preparation Recognizing context and stakeholder needs Using team conflict resolution approaches Preparing for Crucial Conversations® Conflict Facilitation - Clarity Exposing assumptions and biases Defining the conflict and using the CRD Conflict Facilitation - Action Proactive conflict management Conflict facilitation practice Summary and Next Steps Review Personal action plans

Outspoken Cycles Park Tool School courses are aimed at home mechanics who wish to have an in-depth knowledge of their bikes as well as those individuals required to maintain bikes for friends, schools, clubs, businesses and other organisations. The 4 Day Advanced course teaches you advanced mechanical skills following the Park Tool Big Blue Book of Bicycle Repair syllabus in order to help you gain the confidence to take on bicycle repairs involving various manufacturers and systems. Completion of assessment leads to the award of a certificate. You are encouraged to work on your own bike. Please be aware for some elements of the course certain bikes may not be suitable, however, there are also a number of classroom bikes to work on where necessary. We can provide a classroom bike if you’re unable to bring your own.  Course Detail Over four days you will cover: Workshop Practices (Health and Safety, Safe use of tools, PPE, etc.) Tyres & Tubes (Inspection, sizing, systems, puncture repair) Cassettes & Freewheels (types, compatibility, wear, removal and installation) Hub Service (full strip down and rebuild, different systems) Gears and Cabling (identify issues, re-cable, set up and adjustment) Headsets (a-Head and Quill types, strip down and reassemble) Wheel Truing (spoke replacement, introduction to truing, demo wheel construction and lacing) Frame Assessment & Preparation (damage, tools, frame preparation etc.) Bike Setup (choosing the right size bike, saddle height, basic bike fit) Cranksets & Bottom Brackets (different types discussed, removal and replacement) Rim & Disc Brakes (mechanical disc and rim brake set up and adjustment, demo of hydraulic brake bleed) Price The course costs £500 inc VAT. This includes Park Tool Big Blue Book of Bicycle Repair and the use of all tools and equipment while on course.  If you’re a Cambridge Cycling Campaign member, we offer a 15% discount to support the good work that they do. Please email us for access to your coupon code. Refunds for courses are only given under exceptional circumstances and never within 7 days of the advertised course. In the unlikely event we have to make the difficult decision to cancel a course, participants will be offered a refund or the option to reschedule. Please read our terms and conditions for full details. Pre-requisites Course participants must be 18 years old or above. We may be able to accommodate younger participants 16+, we accept these on a case by case basis based on prior experience. Please contact us to discuss. Participants should have a good knowledge of the key content outlined in the Basic: Ride With Confidence and Intermediate courses before booking the Advanced course as this level of knowledge is assumed by the instructor on the day. There will be a brief refresher, but if you are unsure do get in touch to discuss. Course Timings, Assessment, Location & Travel Courses run 9am-4pm over four days, or 9:30am – 4:30pm for weekend courses. Courses take place in our dedicated training workshop at our offices in Cambridge. We have an abundance of bike racks, and we are close to Cambridge North Station. There is limited parking on site on a first-come-first-served basis and we are close to parking at Cambridge North Station. There is some limited on-road parking (at owners risk). You may also park for free at the Milton Park & Ride, which is only a short 15 minute cycle to our workshop.  Further details If you have any further questions, please do please get in touch to discuss. For more information, please read our Terms & Conditions. I would like to say a big thank you to all the teachers for the knowledge they have given me, I’ve loved learning it – Simon Spry, PTS Advanced Participant July 2022

Course Information Embark on our GLP course offering extensive guidance and pragmatic support tailored for individuals serving as Study Directors or Principal Investigators overseeing non-clinical safety studies on pharmaceuticals, agricultural, and industrial chemicals within the realm of Good Laboratory Practice (GLP). This comprehensive programme extends its benefits to study staff and management operating in GLP-compliant environments. The course extensively covers the current OECD GLP Principles and UK GLP legislation, while also referencing international standards, regulations, and guidelines pertinent to the field. Benefits of this course: Practical help and guidance on the interpretation and application of GLP An opportunity to update your knowledge of GLP with the current interpretation of requirements Access to an experienced panel of speakers Information on how other organisations address GLP issues An opportunity to improve your understanding of the GLP requirements as they are applied in different situations. This course is structured to encourage delegates to: Discuss and develop ideas Solve specific problems Examine particular aspects of GLP Learn from the experience of others. Tutors Tutors will be comprised of (click the photos for biographies): Tim Stiles Consultant, Qualogy Ltd Tony Woodall Head of Quality Assurance, Alderley Analytical Gill Armour Study Monitor Team Leader, AstraZeneca Jane Elliston Senior Quality Assurance Auditor, Battelle UK Vanessa Grant -, - Jeanet Logsted CEO, Scantox Programme Please note timings may be subject to alteration. Day 1 09:00 Registration 09:15 Welcome and Introductions 09:35 Development of Good Laboratory Practice A review of the history of GLP, its current scope and application, with a synopsis of current European and international standards. 10:05 Roles and Responsibilities The responsibilities of study director, test facility, management and study staff in the conduct of a GLP study. 10:45 Break 11:00 The Roles and Responsibilities of the Study Director and Test Facility Management The role of the study director in the management and control of a study, as defined by GLP, and management's roles are explored. 11:45 Multi-site Studies What is a multi-site study and when should such concepts be applied on a study. The role of the study director and principal investigator in the planning, conduct and reporting of multi-site study are explored. 12:30 Study Plan (Protocols) GLP requirements for the preparation of a study plan, content, authorisation, amendments and deviations are discussed. 13:00 Lunch 13:45 Workshop 1 - The Study Plan Some practical problems with study plans and amendments explored. 14:45 Workshop 1 - Feedback 15:00 Standard Operating Procedures The control, content and authorisation of SOPs and the principles behind the practice. 15:30 Break 15:45 Workshop 2 - Practical Study Conduct Problems Dealing with practical problems encountered during the conduct of studies. 16:40 Workshop 2 - Feedback 17:15 Close of Day Day 2 09:00 Questions and Answers Discussion of issues raised by course delegates. 09:20 Quality Assurance The interactions between QA, management, study director and principal Investigator are discussed as is QAs role when conducting a multi-site study. 10:00 The Final Report The content of the final report and the role of those involved in its preparation and approval. Specific reporting requirements when conducting a multi-site study are also explained. 10:30 Break 10:45 Workshop 3 - Final Report Problems Practical problems of report preparation including compliance statements. 11:30 Workshop 3 - Feedback 12:00 Management of Raw Data and Records A view on how records and materials are managed and archived in compliance with GLP. 12:45 Lunch 13:30 Workshop 4 - Data and Sample Management Issues Dealing with data and sample management issues. 14:15 Workshop 4 - Feedback 14:45 Regulatory Inspection Government monitoring for compliance with Good Laboratory Practice. 15:15 Panel Session This panel session will address any outstanding issues raised by delegates. 15:45 Close of Course Extra Information Face-to-face course Course Material Course material will be available in PDF format for delegates attending this course. The advantages of this include: Ability for delegates to keep material on a mobile device Ability to review material at any time pre and post course Environmental benefits – less paper being used per course. The material will be emailed in advance of the course and RQA will not be providing any printed copies of the course notes during the training itself. Delegates wishing to have a hard copy of the notes should print these in advance to bring with them. Alternatively delegates are welcome to bring along their own portable devices to view the material during the training sessions. Remote course Course Material This course will be run completely online. You will receive an email with a link to our online system, which will house your licensed course materials and access to the remote event. Please note this course will run in UK timezone. The advantages of this include: Ability for delegates to keep material on a mobile device Ability to review material at any time pre and post course Environmental benefits – less paper being used per course Access to an online course group to enhance networking. You will need a stable internet connection, a microphone and a webcam. CPD Points 14 Points Development Level Develop

This course has been specifically designed to assist professionals applying for Real Estate positions where a Real Estate Financial Modelling test is a requisite part of the interview process.

  During this training course, delegates will acquire the knowledge and skills to plan and carry out internal and external audits in compliance with ISO 19011 and ISO/IEC 17021-1 certification process. Based on practical exercises, you will learn audit techniques and become competent to manage an audit program, audit team, communication with customers, and understand reporting requirements. After acquiring the necessary expertise to perform this audit, you can sit for the exam and gain the "Certified ISO 13485 Lead Auditor' Certificate. By holding this Certificate, delegates can demonstrate that they have the competencies to audit organizations based on best practices. About This Course   Learning Outcomes   Review a Medical Devices Quality Management System based on ISO 13485 Acknowledge the correlation between ISO 13485 and other standards and regulatory frameworks Understand an auditor's role to: plan, lead and follow-up on a management system audit in accordance with ISO 19011 Learn how to lead an audit and audit team Learn how to interpret the requirements of ISO 13485 in the context of a MDQMS audit Acquire the competencies of an auditor to: plan an audit, lead an audit, draft reports, and follow-up on an audit in compliance with ISO 19011   Course Agenda   Day 1: Introduction to Medical Devices Quality Management Systems (MDQMS) and ISO 13485 Day 2: Audit principles, preparation and launching of an audit Day 3: On-site audit activities Day 4: Closing the audit and final exam.   Assessment     Delegates sit a combined exam, consisting of in-course quizzes and exercises, as well as a final essay style exam, consisting of 12 questions, on Day 4 of the course. The overall passing score is 70%, to be achieved within the 150 minute time allowance. Exam results are provided within 24 hours, with both a Certificate and a digital badge provided as proof of success.   Prerequisites   An understanding of ISO 13485 requirements and knowledge of audit principles. What's Included?   Certification fees are included on the exam price Training material containing over 500 pages of information and practical examples will be distributed An attestation of course completion worth 32 CPD (Continuing Professional Development) credits will be issued to the participants who have attended the training course. Who Should Attend?   Auditors seeking to perform Medical Devices Quality Management System (MDQMS) certification audits Managers or consultants seeking to understand the Medical Devices Quality Management System audit requirements Individuals responsible for maintaining conformance with Medical Devices Quality Management System requirements Accreditation Provided by   This course is Accredited by NACS and Administered by the IECB

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Certified Associate in Project Management (CAPM)® Exam Prep This course gives you the knowledge you need to pass the exam and covers CAPM®-critical information on project management theory, principles, techniques, and methods Are you planning on taking the CAPM® examination? This course gives you the knowledge you need to pass the exam and covers CAPM®-critical information on project management theory, principles, techniques, and methods. You'll also have an opportunity for practical applications and time to review the kinds of questions you'll find in the CAPM® Exam. What you Will Learn Apply for the CAPM® Examination Develop a personal exam preparation plan Describe the structure, intent, and framework principles of the current edition of the PMBOK® Guide Explain the PMBOK® Guide Knowledge Areas, as well as their inter-relationships with the each other and the Process Groups Getting Started Program orientation The CAPM® certification process Certified Associate in Project Management (CAPM®) Examination Content Outline CAPM® eligibility requirements Code of Ethics and Professional Conduct Application options Foundation Concepts Skills and qualities of a project manager Project management terminology and definitions Relationship of project, program, portfolio, and operations management Project lifecycle approaches Project Integration Management Review Project Integration Management Knowledge Area Develop Project Charter Develop Project Management Plan Direct and Manage Project Work Manage Project Knowledge Monitoring and Controlling Perform Integrated Change Control Close Project or Phase Project Stakeholder Management Review Project Stakeholder Management Knowledge Area Identify Stakeholders Plan Stakeholder Engagement Manage Stakeholder Engagement Monitor Stakeholder Engagement Project Scope Management Review Project Scope Management Knowledge Area Plan Scope Management Collect Requirements Define Scope Create WBS Validate Scope Control Scope Project Schedule Management Review Project Schedule Management Knowledge Area Plan Schedule Management Define Activities Sequence Activities Estimate Activity Durations Develop Schedule Control Schedule Project Cost Management Review Project Cost Management Knowledge Area Plan Cost Management Estimate Costs Determine Budget Control Schedule Project Resource Management Review Project Resource Management Knowledge Area Plan Resource Management Estimate Activity Resources Acquire Resources Develop Team Manage Team Control Resources Project Quality Management Review Project Quality Management Knowledge Area Plan Quality Management Manage Quality Control Quality Project Risk Management Review Project Risk Management Knowledge Area Plan Risk Management Identify Risks Perform Qualitative Risk Analysis Perform Quantitative Risk Analysis Plan Risk Responses Implement Risk Responses Monitor Risks Project Communications Management Review Project Communications Management Knowledge Area Plan Communications Management Manage Communications Monitor Communications Project Procurement Management Review Project Procurement Management Knowledge Area Plan Procurement Management Conduct Procurements Control Procurements Summary and Next Steps Program Review Mock CAPM® Exam Getting Prepared for the CAPM® Exam After the CAPM® Exam