During this on-demand session tutor Dr Nikki Osborne discusses: * the 3V's (construct, internal and external validity), * what makes a good hypothesis, * the PREPARE guidelines, * what to think about before designing your experiments including systematic reviews, * sources of bias and how to minimise their impact on your research, * defining the experimental unit, * approaches to maximise the signal to noise ratio, plus calculating the correct sample size, * common sources of variation and how to take them into account in your experimental design, * ARRIVE 2.0 for reporting animal studies. * freely available tools and resources to support individuals to develop their knowledge, understanding and skills further.
During this on-demand session tutor Dr Nikki Osborne discusses: * the historical context for animal use in research, * the range of Societal viewpoints on the use of animals in research and ethical theories unpinning them, * how animal use in scientific procedures legislation takes into account 'social ethics' through the process of ethical review, * the 3Rs principles of humane experimental technique. * freely available tools and resources to support individuals to develop their knowledge, understanding and skills further.
Build 9 projects to master 2 essential and modern technologies: Python and PostgreSQL
This course covers the basic concepts of machine learning (ML) that are crucial for getting started on the journey of becoming a skilled ML developer. You will become familiar with different algorithms and networks, such as supervised, unsupervised, neural networks, Convolutional Neural Network (CNN), and Super-Resolution Convolutional Neural Network (SRCNN), needed to develop effective ML solutions.
Learn Python Programming using a Step By Step Approach with 200+ code examples.
Learn how to implement EC2 and VPC resources on AWS using the Python API: Boto3! Implement your infrastructure with code!
Overview This comprehensive course on Data Science with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science with Python 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 Data Science with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science with Python 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 3 sections • 6 lectures • 01:15:00 total length •Module 01: Introduction to Python Data Science: 00:03:00 •Module 02: Environment Setup: 00:10:00 •Module 01: Numpy package for calculations: 00:16:00 •Module 02: Panda package for Data cleaning: 00:19:00 •Module 01: Matplotlib Data Visualization Part 1: 00:16:00 •Module 02: Matplotlib Data Visualization Part 2: 00:11:00
Overview This comprehensive course on Spatial Data Visualization and Machine Learning in Python Level 4 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Spatial Data Visualization and Machine Learning in Python Level 4 comes with accredited certification from CPD, 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? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Spatial Data Visualization and Machine Learning in Python Level 4. It is available to all students, of all academic backgrounds. Requirements Our Spatial Data Visualization and Machine Learning in Python Level 4 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 8 sections • 21 lectures • 04:40:00 total length •Introduction: 00:14:00 •Python Installation: 00:03:00 •Installing Bokeh: 00:04:00 •Data Preparation: 00:24:00 •Creating a Bar Chart: 00:18:00 •Creating a Line Chart: 00:12:00 •Creating a Doughnut Chart: 00:22:00 •Creating a Magnitude Plot: 00:31:00 •Creating a Geo Map Plot: 00:20:00 •Creating a Grid Plot: 00:12:00 •Data Pre-processing: 00:21:00 •Building a Predictive Model: 00:21:00 •Building a Prediction Dataset: 00:07:00 •Adding predicted data to our plots - Part 1: 00:13:00 •Adding predicted data to our plots - Part 2: 00:14:00 •Adding predicted data to our plots - Part 3: 00:15:00 •Adding the Grid Plot: 00:08:00 •Installing Visual Studio Code: 00:01:00 •Creating the Project and Virtual Environment: 00:08:00 •Building and Running the Server: 00:12:00 •Resources: 00:00:00