Here’s what you’re going to learn:
- Hard Skills Vs Soft Skills - What’s the Difference?
- Why Should You List Your Skills on a Resume?
- 8 Best Skills to Put on a Resume
- How to List Skills on a Resume
- 120+ Skills to Put on Your Resume (For 10+ Fields)
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Listing skills on your resume is fairly easy. Listing the right skills in the right way is a little bit trickier. Are you mentioning the right skills for the job, or are you boring the HR manager with irrelevant information? The hiring manager for the software development team couldn’t care less about your expertise in marketing. What they’re dying to know, though, is your skill level in Python and how you get along with the team. In this guide, we’re going to walk you through the process of putting skills on your resume from start to finish. We’ll explain how to identify the right skills and how to list them in a way that catches the hiring manager’s attention!
Here’s what you’re going to learn:
- Keywords:
- Applications for positions Job hunting Résumés (Employment)
- Resource Type:
- Others
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e-book
"A Byte of Python" is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
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e-book
A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the “natural environment” of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful “pipe” operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.
- Subjects:
- Biology
- Keywords:
- Computational biology Textbooks
- Resource Type:
- e-book
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Courseware
In this course, you will learn advanced applications of Python for developing and customizing GIS software, designing user interfaces, solving complex geoprocessing tasks, and leveraging open source. The course consists of readings, walkthroughs, projects, quizzes, and discussions about advanced GIS programming concepts and techniques, and a final term project. Software covered in the course includes: Esri ArcGIS Pro/arcpy, Jupyter Notebook, Esri ArcGIS API for Python, QGIS, GDAL/OGR.
- Subjects:
- Land Surveying and Geo-Informatics
- Keywords:
- Python (Computer program language) Geographic information systems
- Resource Type:
- Courseware
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Others
Take your SQL skills to the next level.
- Subjects:
- Computing
- Keywords:
- Database management SQL (Computer program language)
- Resource Type:
- Others
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Others
Algorithm Visualizer is an interactive online platform that visualizes algorithms from code. Learning an algorithm gets much easier with visualizing it.
- Subjects:
- Computing
- Keywords:
- Algorithms Information visualization
- Resource Type:
- Others
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e-book
Este libro está dirigido, principalmente, a Estudiantes y Docentes que quieren aprender a programarcomo forma de fortalecer sus capacidades cognoscitivas y así obtener un beneficio adicional de su computador para lograr un mejor provecho de sus estudios. Dada la orientación del libro respecto a programar para resolver problemas asociados a las Ciencias e Ingenierías, el requisito mínimo de matemáticas que hemos elegido para presentar el contenido del mismo se cubre, normalmente, en el tercer año del bachillerato. No obstante, el requisito no es obligatorio para leer el libro en su totalidad y adquirir los conocimientos de programación obviando el contenido matemático.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
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Courseware
ArchiStar Academy has world class software and training for architects, engineers and universities students.
- Subjects:
- Computing
- Keywords:
- Design Technology
- Resource Type:
- Courseware
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Others
Brilliant helps you see concepts visually and interact with them, and poses questions that get you to think. Our courses show you that math, science, and computer science are – at their core – a way of thinking. All of our courses are crafted by award-winning teachers, researchers, and professionals from MIT, Caltech, Duke, Microsoft, Google, and more, with these principles of learning in mind. Get started as a beginner with the fundamentals, or dive right into the intermediate and advanced courses for professionals. Brilliant is for ambitious and curious people ages 10 to 110.
- Keywords:
- Science -- Study teaching Technical education Technology -- Study teaching
- Resource Type:
- Others
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MOOC
This is CS50x , Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan, CS50x teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, Python, SQL, and JavaScript plus CSS and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. The on-campus version of CS50x , CS50, is Harvard's largest course.
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science
- Resource Type:
- MOOC
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Courseware
This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
- Course related:
- COMP3011 Design and Analysis of Algorithms, COMP1001 Problem Solving Methodology in Information Technology, COMP4434 Artificial Intelligence, and COMP2011 Data Structures
- Subjects:
- Human-Computer Interaction and Computing
- Keywords:
- Computer programming Computer science Python (Computer program language) Artificial intelligence
- Resource Type:
- Courseware
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Others
Causal Inference for The Brave and True
- Course related:
- MM501 Research Methods
- Subjects:
- Statistics and Research Methods
- Keywords:
- Social sciences -- Statistical methods
- Resource Type:
- Others
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Others
Learn to Code for Free. We're here to make coding more accessible, so everyone can learn the skills they need to upgrade their careers. For example, you can learn Python, HTML, CSS, and JavaScript.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers)
- Resource Type:
- Others
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Video
In 40 episodes, Carrie Anne Philbin teaches you computer science! This course is based on introductory college-level material as well as the AP Computer Science Principles guidelines. By the end of this course, you will be able to: *Outline the history of computers and the design decisions that gave us modern computers *Describe the basic elements of programming and software *Identify the basic components of computer hardware and what they do *Describe how computers are used and how that has evolved over time *Appreciate how far computers have come and how far they might take us
- Course related:
- AMA2222 Principles of Programming
- Subjects:
- Computing
- Keywords:
- Computer science
- Resource Type:
- Video
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MOOC
This course is designed to teach you the foundations in order to write simple programs in Python using the most common structures. No previous exposure to programming is needed. By the end of this course, you'll understand the benefits of programming in IT roles; be able to write simple programs using Python; figure out how the building blocks of programming fit together; and combine all of this knowledge to solve a complex programming problem. We'll start off by diving into the basics of writing a computer program. Along the way, you’ll get hands-on experience with programming concepts through interactive exercises and real-world examples. You’ll quickly start to see how computers can perform a multitude of tasks — you just have to write code that tells them what to do.
- Course related:
- COMP1001 Problem Solving Methodology in Information Technology
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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Others
Python can be easy to pick up whether you're a first time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way writing programs with Python!
- Subjects:
- Computing
- Keywords:
- Computer programming Python (Computer program language) Information visualization Computer science
- Resource Type:
- Others
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Courseware
This course is for all of those struggling with data analysis. You will learn: - Overcome data analysis challenges in your work and research - Increase your productivity and make better business decisions - Enhance your data analysis skills using spreadsheets - Learn about advanced spreadsheet possibilities like array formulas and pivottables - Learn about Excel 2013 features like PowerPivot & PowerMap - Learn to organize and test your spreadsheets
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MOOC
Data science has critical applications across most industries, and is one of the most in-demand careers in computer science. Data scientists are the detectives of the big data era, responsible for unearthing valuable data insights through analysis of massive datasets. And just like a detective is responsible for finding clues, interpreting them, and ultimately arguing their case in court, the field of data science encompasses the entire data life cycle. That starts with capturing lots of raw data using data collection techniques, and then building and maintaining data pipelines and data warehouses that efficiently “clean” the data and make it accessible for analysis at scale. This data infrastructure allows data scientists to efficiently process datasets using data mining and data modeling skills, as well as analyze these outputs with sophisticated techniques like predictive analysis and qualitative analysis. Finally, these findings must be presented using data visualization and data reporting skills to help business decision makers. Depending on the size of the company, data scientists may be responsible for this entire data life cycle, or they might specialize in a particular portion of the life cycle as part of a larger data science team
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Big data
- Resource Type:
- MOOC
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MOOC
The building industry is exploding with data sources that impact the energy performance of the built environment and health and well-being of occupants. Spreadsheets just don’t cut it anymore as the sole analytics tool for professionals in this field. Participating in mainstream data science courses might provide skills such as programming and statistics, however the applied context to buildings is missing, which is the most important part for beginners. This course focuses on the development of data science skills for professionals specifically in the built environment sector. It targets architects, engineers, construction and facilities managers with little or no previous programming experience. An introduction to data science skills is given in the context of the building life cycle phases. Participants will use large, open data sets from the design, construction, and operations of buildings to learn and practice data science techniques. Essentially this course is designed to add new tools and skills to supplement spreadsheets. Major technical topics include data loading, processing, visualization, and basic machine learning using the Python programming language, the Pandas data analytics and sci-kit learn machine learning libraries, and the web-based Colaboratory environment. In addition, the course will provide numerous learning paths for various built environment-related tasks to facilitate further growth.
- Keywords:
- City planning -- Statistical methods Python (Computer program language) Information visualization
- Resource Type:
- MOOC
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Others
Make great data visualizations. A great way to see the power of coding!
- Subjects:
- Computing
- Keywords:
- Information visualization Python (Computer program language)
- Resource Type:
- Others
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