1357 Scientist courses

During this on-demand session tutor Dr Nikki Osborne discusses: * what is welfare, the five freedoms & 'a life worth living' * why animal welfare is important - scientifically & ethically * how our understanding of a good life for laboratory animals is changing, * the laboratory animal's lifetime experience, * what refinement requires in practice & factors to consider, * sources of laboratory animals, plus husbandry & care, * the importance of good animal handling & knowing what is 'normal', * experimental procedures & assessing welfare, * humane endpoints & methods of killing * the refinement loop & marginal gains. * 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 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: * What research integrity is, and who is responsible for what? * the research framework as it relates to the responsible use of live animals or animal derived materials in Life Science research, * good practice expectations regarding openness and transparency, plus the dissemination of research outputs, * real-life examples of research misconduct within the life science sector, plus common non-compliance issues with UK and EU legislation governing the use of animals in scientific procedures. * 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.

Machine Learning is reshaping industries faster than you can say "algorithm". Our Machine Learning with Python Course is built for those who are genuinely curious about how machines learn, make decisions, and improve with data. With Python as your trusty companion, you’ll explore the key concepts and core techniques behind predictive modelling, supervised and unsupervised learning, and data-driven algorithms—all explained in a clear and digestible manner. No fluff, no filler—just solid learning with a structured approach. You’ll journey through essential modules that guide you from the fundamentals of machine learning to building models that actually do something meaningful. Whether you're brushing up your CV or aiming to understand how systems like recommendation engines or fraud detection work, this course offers insight that clicks. Python’s role in the process isn’t treated as a side note—it's woven through each section so you're building knowledge that’s both relevant and up-to-date in today’s data-focused world. If you’re ready to treat your brain to some serious logic and clever code, then this course has your name written in Pythonic syntax. Learning Outcomes: Understand the fundamentals of machine learning. Manipulate data using Numpy and Pandas libraries. Build and evaluate machine learning models using Sklearn pipeline and column transformer. Explore the world of data analysis with Pandas DataFrame. Contribute to the development of cutting-edge technology in the field of machine learning. The Machine Learning with Python course is designed to provide you with the skills and knowledge needed to develop and evaluate machine learning models using Python. In this course, you'll learn how to manipulate data using Numpy and Pandas libraries, build and evaluate machine learning models using Sklearn pipeline and column transformer, and explore the world of data analysis with Pandas DataFrame. The course is perfect for aspiring data scientists, machine learning engineers, and developers interested in machine learning development. By the end of this course, you'll have a deep understanding of the fundamentals of machine learning and how to contribute to the development of cutting-edge technology in this exciting field. With hands-on experience in manipulating data and building and evaluating machine learning models, you'll be well-equipped to start a career in machine learning. Machine Learning with Python Course Course Curriculum Section 01: Introduction Section 02: Numpy Library Section 03: Matplotlib Section 04: Polynomial Regression How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring data scientists. Machine learning engineers. Developers interested in machine learning development. Anyone interested in the field of machine learning. Professionals looking to upskill in the latest technology. Career path Aspiring data scientists. Machine learning engineers. Developers interested in machine learning development. Anyone interested in the field of machine learning. Professionals looking to upskill in the latest technology. Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

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