19 Bioinformatics courses

Give a compliment to your career and take it to the next level. This Biomedical Engineering will provide you with the essential knowledge to shine in your professional career. Whether you want to develop skills for your next job or elevate skills for your next promotion, this Biomedical Engineering will help you keep ahead of the pack. The Biomedical Engineering incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your expertise and essential knowledge, which will assist you in reaching your goal. Further, this Biomedical Engineering will add extra value to your resume to stand out to potential employers. Throughout the programme, it stresses how to improve your competency as a person in your chosen field while also outlining essential career insights in this job sector. Consequently, you'll sharpen your knowledge and skills; on the other hand, see a clearer picture of your career growth in future. By the end of the Biomedical Engineering, you can equip yourself with the essentials to keep you afloat in the competition. Along with this Biomedical Engineering course, you will get 10 premium courses, an original hardcopy, 11 PDF Certificates (Main Course + Additional Courses) Student ID card as gifts. This Biomedical Engineering Bundle Consists of the following Premium courses: Course 01: Biomedical Science Course 02: European Medical Device Regulations Course 03: Public Health Course 04: Human Anatomy and Physiology Course 05: Epidemiology Course 06: Diploma In Microbiology Course 07: Microbiology Technician Course Course 08: Digital Electric Circuits & Intelligent Electrical Devices Course 09: Electrical and Fire Safety Training - Level 2 Course 10: Emergency First Aid and Incident Management at Work Course 11: Creativity and Problem Solving Skills As one of the top course providers in the UK, we're committed to providing you with the best educational experience possible. Our industry experts have designed the Biomedical Engineering to empower you to learn all at once with accuracy. You can take this comprehensive Biomedical Engineering Bundle course at your own pace - anytime, from anywhere. So, enrol this premium Biomedical Engineering now to advance your career! Curriculum of Biomedical Engineering Bundle Course 01: Biomedical Science Introduction to Biomedical Science What is Biomedical Science? Definition of Biotechnology Anatomy, Physiology and Pathology Microbiology and Cell Biology Toxicology and Pharmacology Virology, Bacteriology and Immunology Biochemistry and Molecular Biology Genetics Bioinformatics Genetics and Biochemistry Concepts and Overview Genes and Human Genome DNA and RNA Genetic Transmission Pattern Gene Mutation Amino Acids - Structure & Function Protein - Structure & Function Protein Synthesis Microbiology and Cell Biology Microbial Nutrition and Growth VIRUS Bacteria Immunology Antigen and Antibody Cells and Tissues Metabolism Biochemical Engineering and Enzyme Discovery Biotechnology Cell Fusion Biological Process Enzyme Kinetics Industrial Applications of Enzymes Carbohydrates Plant Cell Cultivations Toxicology, Pharmaceuticals and Fine Chemicals Toxicology Sources of Toxic Compounds Movement of Toxicants in the Environment Pharmaceutical Fine Chemicals Pharmaceutical Active Ingredients Peptides, Nucleotides and Saccharides Systems and Synthetic Biology Synthetic Biology Significant Breakthrough in Metabolic Engineering Biological Networks Metabolic Networks Protein-Protein Interaction Networks Metabolic Engineering Global Health Challenges What is Global Health Importance of Global Health Global Health Challenges ----------- 10 additional Biomedical Engineering Related Courses----------- Certificates after Completion of Biomedical Engineering Bundle: PDF Certificate: Free (Previously it was £6*10 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) CPD 110 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Biomedical Engineering bundle. ** Completing this course does not imply that you are qualified to work as a Biomedical Scientist. If you are seeking a course that fits the HCPC's standards, please contact the HCPC or the RCSLT ** Requirements Our Biomedical Engineering is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices. Career path Having this various Biomedical Engineering expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included

In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNNs). You will learn how to apply CNNs to several practical image recognition datasets and learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning.

In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.

In this self-paced course, you will learn how to use TensorFlow 2 to build deep neural networks. You will learn the basics of machine learning, classification, and regression. We will also discuss the connection between artificial and biological neural networks and how that inspires our thinking in deep learning.

Get started with Neural networks and understand the underlying concepts of Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. This hands-on course will help you understand deep learning in detail with no prior coding or programming experience required.

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

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Learn the essential knowledge and build solid skills in biotechnology with the Biotechnology course. This course will enrich your understanding of biology and present you with job opportunities in the field of business, healthcare, and other industries. Within no time, you will become competent and confident to establish a brilliant career. The Biotechnology course is divided into easy to follow bite-sized modules to help you understand every topic without difficulties. Here, you will learn the core principles and the history of biotechnology. The informative lectures will educate you on molecular and cellular biotechnology. In addition, you will receive the ability to identify the differences between biotechnology and molecular biology. This comprehensive course will also help you grasp the fundamentals of genetic engineering.  Through this Biotechnology course, you will understand the significance of biology in different industries, healthcare sectors and business sectors. At the end of this course, you will receive a valuable certificate, which you'll elevate your resume and boost your employability in the relevant sector. Enrol today! Please note: Our Biotechnology course only gives you theoretical knowledge to excel in this field. This course doesn't entitle you to practise as a professional in this specific field. Learning Objectives Get introduced to the basics of biotechnology Learn about the history of biotechnology Enrich your knowledge of molecular and cellular biology Understand the difference between biotechnology and molecular biology Grasp the principles of genetic engineering Know the fundamental of industrial biotechnology Understand the role of biotechnology in the health and business sector Who is this Course for? This Biotechnology course is ideal for aspiring biotechnologists who wish to gain the relevant skills and knowledge to fast track their careers. It is for those who have little or no knowledge of the principles of biotechnology or those who are new to the field and want to test their skills and knowledge. There are no entry requirements for this course; however, an eye for detail and a creative mind is essential. Entry Requirement Anyone interested in learning more about this subject should take this Biotechnology course. 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 £4.99 and the hard copy for £9.99. Also, you can order both PDF and hardcopy certificates for £12.99. Career path On successful completion of the Biotechnology course, learners can progress to a more advanced program from our course list. Career opportunities in this field include freelancing or working in-house, within a range of professional settings, with the opportunity to earn a high salary. Related professions in this industry include: Biomedical Engineer Biochemist Clinical Technician Microbiologist Process Development Scientist Biomanufacturing Specialist Business Development Manager Medical Lab Technologist Microbiologist Clinical Support Specialist Course Curriculum Module 1 - Introduction to Biotechnology Introduction to Biotechnology 00:19:00 Module 2- Biotechnology in the Realm of History Biotechnology in the Realm of History 00:27:00 Module 3- Molecular and Cellular Biology Molecular and Cellular Biology 00:27:00 Module 4 - Biotechnology Versus Molecular Biology Biotechnology Versus Molecular Biology 00:11:00 Module 5- Genetic Engineering Genetic Engineering 00:16:00 Module 6- Biotechnology in Health Sector Biotechnology in Health Sector 00:11:00 Module 7- Industrial Biotechnology Industrial Biotechnology 00:14:00 Module 8- Biotechnology in a Business Perspective Biotechnology in a Business Perspective 00:13:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

About Course Master the statistical skills you need to understand and analyze biomedical research data with this Biostatistics Online Course Are you working on public health, clinical medicine, biology or related fields? Are you familiar with the process of obtaining an accurate picture from a large number of data points? This Biostatistics Online Course demonstrates how to use statistical techniques to summarize the characteristics of a data set to draw meaningful conclusions. In this course, you will learn all about Biostatistics and its application in medical and life sciences. This course is a comprehensive introduction to the field of biostatistics, covering a wide range of topics from basic statistical concepts to more advanced biostatistical methods.Biostatistics Online Course modules: Module 1: Introduction to Biostatistics This module provides an overview of biostatistics, its applications in the field of health sciences, and the different types of study designs used in biomedical research. It also introduces the basic concepts of statistics, including data types, variables, inferential statistics, hypothesis testing, and the role of statistics in biostatistics and evidence-based medicine. Module 2: Probability This module covers the basics of probability, including probability distributions, random variables, and sampling distributions. Students will learn how to calculate and interpret probabilities in the context of biomedical research. Module 3: Descriptive Statistics This module covers the different measures of central tendency and variability, as well as graphical representations of data. Students will learn how to describe and summarize data from biomedical studies using these methods. Module 4: Inferential Statistics This module covers the fundamental concepts of inferential statistics, including estimation, hypothesis testing, confidence intervals, and p-values. Students will learn how to use these methods to draw conclusions about populations based on data from samples. Module 5: Regression Analysis This module introduces the basics of regression analysis, including simple linear regression, multiple linear regression, and logistic regression. Students will learn how to use these methods to model relationships between variables and to make predictions. Module 6: Biostatistics Tools This module covers a variety of biostatistical tools that are commonly used in biomedical research, including survival analysis, clinical trials, and epidemiological studies. Students will learn how to use these tools to answer specific research questions. Module 7: Statistical Software and Tools This module introduces students to popular statistical software programs, such as R and SPSS. Students will learn how to import, manage, and analyze data using these software programs, as well as how to perform statistical tests and generate summary statistics. Module 8: Ethical Considerations and Reporting Guidelines This module covers the importance of ethical considerations in biostatistics and the reporting guidelines for statistical analysis in research publications. Students will also learn about best practices for data management and data sharing. Why You Should Take This Course Whether you are a student, researcher, or healthcare professional, biostatistics is an essential skill for understanding and interpreting biomedical research. This course provides a comprehensive and accessible introduction to the field of biostatistics, covering all the essential topics that you need to know. By taking this course, you will learn how to: Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively This course is ideal for students in the fields of public health, medicine, nursing, epidemiology, and other health sciences. It is also beneficial for researchers, healthcare professionals, and anyone else who wants to learn more about biostatistics. Enroll today and start your journey to becoming a biostatistics expert! To find more course in this topic, search more . What Will You Learn? Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively Course Content Introduction to Biostatistics Introduction to Biostatistics Probability Module 2 Probability Descriptive Statistics Descriptive Statistics Inferential Statistics Inferential Statistics Regression Analysis Regression Analysis Biostatistics Tools Biostatistics Tools Statistical Software and Tools Statistical Software and Tools Ethical Considerations and Reporting Guidelines Ethical Considerations and Reporting Guidelines A course by Xpert Learning RequirementsBasic understanding of Mathematics and Statistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics