Courses tagged with "Evaluation" (171)
Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gentler-paced alternative to the first course in our Bioinformatics Specialization (Finding Hidden Messages in DNA).
¿Alguna vez pensaste en crear tus propios juegos de computadora, pero no tenías idea cómo hacerlo o por dónde comenzar? Este curso te enseñará a programar utilizando Scratch, un lenguaje de programación visual muy fácil de usar, y más importante aún, aprenderás los principios fundamentales de la computación para que comiences a pensar como ingeniero/a de software.
This course is designed as an introduction to computer programming using Java. Students will learn how to a) analyze a problem, and identify and define the computing requirements appropriate to its solution b) design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs, and c) apply design and development principles in the construction of software systems of varying complexity. Topics include Computers, programs, Java, input and output, identifiers, variables, assignment statements, constants, memory diagrams, primitive data types, conditional statements, repetition, methods, parameters, arguments, return values, one dimensional arrays, objects, classes, and classes from the Java Application Programmers Interface (API).
Kursbeschreibung
Der Kurs führt in das zentrale Gebiet der Informatik ein, auf dem alle anderen Teilgebiete aufbauen: Wie entwickele ich Software? Anhand der Programmiersprache Java werden Algorithmen zum Suchen und Sortieren vorgestellt und die dazu benötigten Datenstrukturen wie Keller, Schlange, Liste, Baum und Graph eingeführt.
Was lerne ich in diesem Kurs?
Die Teilnehmer des Kurses werden in die Lage versetzt, eine Problemstellung auf maschinelle Lösbarkeit hin zu analysieren, dafür einen Algorithmus zu entwerfen, die zugehörigen Datenstrukturen zu wählen, daraus ein Java-Programm zu entwickeln und dieses zur Lösung des Problems einzusetzen.
Welche Vorkenntnisse benötige ich?
Mathematikkenntnisse auf Oberstufenniveau.
Kursplan
Kapitel | Thema |
---|---|
Kapitel 1 | Einführung |
Kapitel 2 | Systemumgebung |
Kapitel 3 | Java |
Kapitel 4 | Datentypen |
Kapitel 5 | Felder |
Kapitel 6 | Methoden |
Kapitel 7 | Rekursion |
Kapitel 8 | Komplexität |
Kapitel 9 | Sortieren |
Kapitel 10 | Objektorientierung |
Kapitel 11 | Abstrakte Datentypen |
Kapitel 12 | Suchbäume |
Kapitel 13 | Hashing |
Kapitel 14 | Graphen |
Algorithms power the biggest web companies and the most promising startups. Interviews at tech companies start with questions that probe for good algorithm thinking.
In this computer science course, you will learn how to think about algorithms and create them using sorting techniques such as quick sort and merge sort, and searching algorithms, median finding, and order statistics.
The course progresses with Numerical, String, and Geometric algorithms like Polynomial Multiplication, Matrix Operations, GCD, Pattern Matching, Subsequences, Sweep, and Convex Hull. It concludes with graph algorithms like shortest path and spanning tree.
Topics covered:
- Sorting and Searching
- Numerical Algorithms
- String Algorithms
- Geometric Algorithms
- Graph Algorithms
This course is part of the Fundamentals of Computer Science XSeries Program:
Learn various methods of analysis including: unsupervised clustering, gene-set enrichment analyses, Bayesian integration, network visualization, and supervised machine learning applications to LINCS data and other relevant Big Data from high content molecular and phenotype profiling of human cells.
This is the second course in a two-part series on bioinformatics algorithms, covering the following topics: evolutionary tree reconstruction, applications of combinatorial pattern matching for read mapping, gene regulatory analysis, protein classification, computational proteomics, and computational aspects of human genetics.
6.00.2x will teach you how to use computation to accomplish a variety of goals and provides you with a brief introduction to a variety of topics in computational problem solving . This course is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity. You will spend a considerable amount of time writing programs to implement the concepts covered in the course. For example, you will write a program that will simulate a robot vacuum cleaning a room or will model the population dynamics of viruses replicating and drug treatments in a patient's body.
Topics covered include:
- Advanced programming in Python 3
- Knapsack problem, Graphs and graph optimization
- Dynamic programming
- Plotting with the pylab package
- Random walks
- Probability, Distributions
- Monte Carlo simulations
- Curve fitting
- Statistical fallacies
Information Technology (IT) is everywhere. Every aspect of human activity depends on it. All IT processes, whether they drive mobile phones, the Internet, transportation systems, enterprise systems, publishing, social networks or any other application, rely on software.
In this new and improved version of the course, you will learn to write software with a progressive hint system for first time programmers. The core skill is programming; not just the ability to piece together a few “lines of code,” but writing quality programs, which will do their job right, and meet the evolving needs of their users. Anyone can write a program; this course teaches you to write good programs.
The course starts from the basics of computing and takes you through a tour of modern object-oriented programming, including classes, objects, control structures, inheritance, polymorphism, and genericity.
Throughout the course, you will have the opportunity to learn the principles of programming as well as the techniques for designing correct and reliable programs by using the Eiffel programming language and notation. You will be trying out example problems to provide your solution, and see it immediately compiled and tested from within your browser. To this end, we are using the Codeboard;web-based IDE, developed at the Chair of Software Engineering (ETH Zurich).
Beyond programming, you will also get a glimpse at theoretical computer science, the set of mathematical techniques that underlie computation and makes today’s IT-based world possible.
In this third edition of the course we specifically focus on helping students with little or no programming experience. To this end, we have improved the introductory material about the Eiffel language, and we have implemented a progressive hint system students can use to get guidance on how to solve the programming exercises.
"Really good course. Followed it with a couple of experienced colleagues all of them having a computer science background. They really liked the concepts and programming in Eiffel a lot. Many thanks to the team making this course available! Can not wait to start with the advanced course!" --Previous CAMSx Participant
Previous edition course evaluation:
Overall course rating (1: worst grade, 6: best grade):
Grade Resp. %Resp
1 1 2%
2 0 2%
3 3 6%
4 9 18%
5 20 40%
6 17 34%
Total respondents: 50
Average: 4.96
The network is what makes the cloud. The cloud’s key capabilities—the ability to share infrastructure, the ability to move and scale applications across servers, massive parallelism, virtualization, and worldwide connectivity—are all rooted in the network. Learn how it all works!
Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language. More importantly, it will introduce you to the fundamental principles of computing and it will help you think like a software engineer.
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