Courses

Explore the fascinating world of amphibian biology in this engaging video featuring Tyrone Hayes, a professor of Integrative Biology at the University of California at Berkeley. Discover the development process of frogs from eggs to tadpoles to adults, and learn about the harmful effects of chemical fertilizers like atrazine on frog reproduction. Gain insights into how Hayes' research on frogs contributed to breast cancer research. Delve into topics such as environmental health, field simulations, and the concept of environmental racism. Watch as Hayes demonstrates his passion for amphibians and explains the importance of his work in understanding the impact of pesticides on both wildlife and human health.

Learn Python programming tailored for biologists and bioinformatics beginners through a comprehensive tutorial series. Dive into essential concepts such as data types, string manipulation for DNA sequences, and sequence analysis techniques. Master indexing and slicing to extract subsequences, work with lists, and discover how to reverse genetic sequences. Explore the power of functions to reuse sequence analysis code efficiently. Gain practical skills in handling multiple GenBank files and extracting sequences from FASTA files. Equip yourself with the fundamental Python knowledge necessary for bioinformatics applications and genetic data manipulation.

Explore the intersection of biology and Python in this engaging EuroPython Conference talk. Discover how computational biology is transforming research, with Python emerging as a popular language in biosciences due to its clean syntax and extensive modules for various biological domains. Learn about tools like Biopython, Bokeh, Networkx, and Ecopy as the speaker guides you through an adventure into natural sciences. Gain insights into how Python is improving researchers' workflows, allowing them to focus on theory and experiments rather than struggling with outdated applications. Suitable for audiences with or without a biological background, this 25-minute presentation demonstrates the strong relationship between biology and computing, showcasing how technological advances are helping predict physical interactions between atoms and DNA.

Embark on a fascinating journey through the intersection of biology and Python programming in this EuroPython Conference talk. Discover how computational biology is transforming research, with Python emerging as a popular language in biosciences due to its clean syntax and extensive modules for various biological domains. Explore tools like Biopython, Bokeh, Networkx, and Ecopy as you delve into topics such as avocado prices, virus behavior, ant colony optimization, neural networks, and the World Happiness Report. Learn how Python is improving researchers' workflows and enabling better understanding of our environment through the integration of biological information into algorithms. Suitable for audiences with or without a biological background, this talk demonstrates the strong relationship between biology and computing, showcasing how technological advances are revolutionizing the field.

This course will start with Basic principles of NMR, walk through the analysis of spectra and demonstrate the application of multidimensional NMR spectroscopy in Chemistry and structural Biology. INTENDED AUDIENCE: M. Sc./ PhD and Scientists working in Pharma and Biophrma IndustriesPREREQUISITES: Under graduate level understanding of Physics and Mathematics INDUSTRY SUPPORT: Biocon, Wockhardt, Aurobindo Biopharma etc

Explore the computational challenges and cutting-edge solutions in cancer genomic pipelines through this insightful conference talk. Join Samantha Langit, a high school student with a background in Cancer Biology from Stanford, and her mother Lynn Langit, a Cloud architect, as they demonstrate their collaborative work in bioinformatics. Discover how they leverage advanced cloud technologies like Docker and Lambda to push the boundaries of cancer genomic research. Through live demonstrations, gain valuable insights into the latest cloud data pipeline developments for the bioinformatics community, showcasing the powerful intersection of biology and cloud computing in the fight against cancer.

Watch a comprehensive video tutorial on character design as illustrator Chris Blackstock creates an alien wildlife biologist using Photoshop. Follow along as Chris guides you through the entire process, from initial concept and sketching to the final design. Learn valuable techniques for designing faces, using reference materials, and studying anatomy. Explore the creation of a companion creature and the addition of gear to enhance the character. Gain insights into canvas size, DPI, and creating clean lines. Discover Chris's early art influences and hear his thoughts on social media for artists. Join host Codi Bear in this Adobe Live session to expand your character design skills and explore new creative possibilities.

Improve your image analysis knowledge and ability to analyse your images The use of automatic image analysis in the biological sciences has increased significantly in recent years, especially with automated image capture and the rise of phenotyping. This online course will help improve your understanding of image analysis methods, and improve your practical skills and ability to apply the techniques to your images. You will explore the process of image acquisition, through to segmenting regions, counting objects and tracking movement. Importantly, we’ll also try to highlight what to watch out for when using different image analysis approaches. This course is designed for postgraduate and postdoctoral researchers in biological sciences. The use of automatic image analysis in the biological sciences has increased significantly in recent years, especially with automated image capture and the rise of phenotyping. This online course will help improve your understanding of image analysis methods, and improve your practical skills and ability to apply the techniques to your images. Development and delivery of this course is supported by Biotechnology and Biological Sciences Research Council Training Grant BB/P011845/1 Image Analysis for Biologists: An Online Course. The course and practicals refer to the open-source Fiji software (http://fiji.sc/). To use this you will need a computer (rather than a tablet or smartphone). Please see installation instructions at the Fiji website.

Mastering Python for Biological Data, Automation, and Visualization What you'll learn: Set up a robust Python development environment using Anaconda Navigator and efficiently manage packages for bioinformatics applications.Master advanced numeric operations, typecasting, and string manipulation techniques through practical exercises designed to handle complex data transformations.Gain expertise in file handling, data structures, and control flow logic, applied through lots of in-class, hands-on projects.Excel in Biopython, regular expressions, data analysis, and visualization with Pandas, Seaborn, and Matplotlib in real-world bioinformatics projects.Hidden gems and unique techniques for efficient coding. Welcome to "Python for Biologists and Beginners", an engaging and practical course designed to introduce you to Python programming while focusing on its applications in biology and bioinformatics. Whether you're new to coding or looking to expand your programming skills, this course will equip you with the knowledge and tools to analyze biological data, automate tasks, and solve problems in the life sciences.Throughout this course, you’ll learn Python from the ground up, with a special emphasis on concepts and techniques that biologists can use in their research and analysis. The course is structured to build your confidence and skills progressively, allowing you to apply what you’ve learned to real-world biological datasets.Key Features:100+ Videos: Comprehensive lessons covering everything from Python basics to advanced applications in biology.Clear Explanations: Each concept is broken down and explained thoroughly, with coding exercises to reinforce your understanding.Real-world Assignments: These large assignments challenge you to apply your knowledge, with solutions provided to guide your learning.9 Quizzes: Test your progress and understanding with quizzes at key points throughout the course.1 Hands-on Activity: A practical exercise to help you apply your skills to real-world biological data.By the end of the course, you’ll be prepared to use Python for data analysis, automation, visualization, and bioinformatics, making it a perfect fit for biologists looking to enhance their computational skills.

Welcome to Bioinformatics Bootcamp Beginner Topics: R for Biologists! ​This page contains all the lectures and materials needed to participate. For any questions, please contact Henry Miller (Email in Syllabus). You can also stop by the instructor office hours (in syllabus) whether or not you are enrolled synchronously. *Simon's record for XP on DataCamp is 79,160. If you are enrolled and can beat that during the workshop timeframe (by 5PM CST May 3rd, 2021), you will get a prize (to be determined...). Github Workshop Repo HERE Download the Syllabus HERE

This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.

ABOUT THE COURSE:The course aims to bridge the gap between theoretical geomechanics and its applications in real-life geotechnical engineering problems. You will learn to develop mathematical models based on constitutive relations and numerical techniques, e.g., numerical differentiation and integration, which are crucial for the formulation of mathematical problems and data analysis. You will learn to solve ODEs, Eigen Value Problems, and PDEs. You will also learn how to use the finite difference and finite element methods to solve problems related to slope stability, retaining structures, shallow and deep foundation bearing capacity, consolidation settlement, and seepage analysis. Students will develop their own code and use open-source computational tools like LimitStateGEO and OpenSees. We will share assignment problems each week and conduct a pen and pencil exam at the end of the course. This course equips students and practitioners with a fundamental understanding of geomechanics and the necessary numerical skills to tackle complex geomechanics problems. The course will be helpful for students preparing for competitive exams, as well as design practitioners enhancing their professional careers.INTENDED AUDIENCE: UG and PG students. Research Scholars and Practicing Engineers can also take this course.PREREQUISITES: Exposure to Soil Mechanics, Numerical Methods and basic programmingINDUSTRY SUPPORT: Most design companies working in Geotechnical Engineering like L&T, TCE, Reliance Infra, AFCONS, HCC, Keller, Golder Associates, etc

Explore computational genomics through a comprehensive 6-hour course from San Diego State University. Delve into genome sequencing technologies, DNA assembly techniques, and bioinformatics tools. Learn about AWS for genomic analysis, BLAST algorithms, antibiotic resistance mechanisms, and advanced k-mer counting methods. Gain practical skills in metagenome binning, genome consistency checking, and subsystem classification. Suitable for students and professionals seeking to enhance their understanding of modern genomic analysis techniques and their applications in microbiology and antibiotic resistance research.

Explore the fascinating realm of computational habitability in this 37-minute lecture presented by Associate Professor Rory Barnes from UW Astrobiology. Delve into various aspects of planetary science and astrobiology, starting with atmospheric processes such as water photolysis and hydrogen escape. Examine the interior dynamics of planets, focusing on the thermal, magnetic, and volatile evolution of Venus. Investigate surface conditions, including ice coverage on Earth-like exoplanets. Learn about planetary system dynamics, specifically orbital evolution in resonance. Discover the intricacies of planets orbiting tidally evolving binary stars and the obliquities of Teegarden's Star's planets. Conclude with an analysis of the history and habitability of the LP 890-9 planetary system. Gain valuable insights into the computational methods used to assess the potential habitability of various celestial bodies and planetary systems.

This course is an introduction to the area of computational complexity theory. We will see different models of computations and computational complexity classes. The computational models measure various different aspects of computation, like time, space, randomness, number of gates, amount of communication etc. The complexity classes classify different computational problems depending on their easiness or hardness as per these different models. We will also see how these complexity classes are related to each other. Many of the results are extremely interesting and use several interesting ideas.INTENDED AUDIENCE : Students of Computer Science discipline. This could be BTech students who are interested in Theory or MTech/PhD students.PREREQUISITES : Theory of Computation.

Explore the fascinating intersection of human creativity and digital automation in this thought-provoking conference talk from NDC Oslo 2021. Delve into the evolution of computing, from human calculators to modern machine learning, and examine the profound implications for various fields. Investigate complex questions surrounding creativity, attribution, and responsibility in the age of artificial intelligence. Consider real-world scenarios that challenge our understanding of authorship, royalties, and accountability in areas such as entertainment, music, and social media. Join developer, musician, and Rockstar programming language creator Dylan Beattie on an enlightening journey that traverses the boundaries between human innovation and computational creativity, offering insights into the future of technology and its impact on society.

Instructor: Prof. Pankaj Aggarwal, Department of Computer Science and Engineering, IIT Delhi. This course covers lessons in Introduction using Basic Visibility Problems, The Maximal Points Problem, The Plane Sweep Technique and applications, Convex Hull Different Paradigms and Quickhull, Dual Transformation and Applications, Lower Bounds on Algebraic Tree Model, Point Location and Triangulation, Voronoi Diagram and Delaunay Triangulation, Randomized Incremental Construction and Random Sampling, Arrangements and Levels, Range Searching, Clustering Point Sets using Quadtrees and Applications, Epsilon-Nets VC Dimension and Applications, Shape Analysis and Shape Comparison.

Dive into a comprehensive 23-hour course on Computational Geometry, exploring fundamental concepts and advanced techniques through a series of lectures. Begin with introductory topics and progressively delve into more complex subjects, covering a wide range of geometric algorithms and their applications. Learn about geometric data structures, convex hulls, Voronoi diagrams, triangulations, and various computational methods used in solving geometric problems. Gain practical skills in designing and analyzing algorithms for geometric computations, essential for fields such as computer graphics, robotics, and geographic information systems. Through 11 detailed lecture sessions, each divided into multiple parts, develop a strong foundation in this crucial area of computer science and mathematics.

In this course, we will expand on vision as a cognitive problem space and explore models that address various vision tasks. We will then explore how the boundaries of these problems lead to a more complex analysis of the mind and the brain and how these explorations lead to more complex computational models of understanding.

ABOUT THE COURSE:Computational Neuroscience is the fundamental subject to provide quantitative understanding of information processing by neurons in the brain. Questions on, how humans and other animals learn efficiently, create and recall memories, make decisions among many others can be approached with the basic understanding of computation by neurons and its general principles. The course will include topics starting with the very basics of quantifying neuronal activity and modeling spiking by single neurons. Next the course dwells upon the general approaches used to understand representation of information by neurons and how such information may be readout for practical applications. Finally the course covers the computational modeling of implementing plasticity, the most important aspect of the brain, aiding in learning, memory and cognition.INTENDED AUDIENCE: Students interested in Neural and Cognitive Sciences and AIPREREQUISITES: 1st year college Mathematics and BiologyINDUSTRY SUPPORT: AI related industry