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:
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)
15.875 is a project-based course that explores how organizations can use system dynamics to achieve important goals. In small groups, students learn modeling and consulting skills by working on a term-long project with real-life managers. A diverse set of businesses and organizations sponsor class projects, from start-ups to the Fortune 500. The course focuses on gaining practical insight from the system dynamics process, and appeals to people interested in system dynamics, consulting, or managerial policy-making.
Every day, a sea of decisions stretches before us, and it’s impossible to make a perfect choice every time. But there are many ways to improve our chances — and one particularly effective technique is critical thinking. Samantha Agoos describes a 5-step process that may help you with any number of problems.
A Brief Introduction to Engineering Computation with MATLAB is specifically designed for students with no programming experience. However, students are expected to be proficient in First Year Mathematics and Sciences and access to good reference books are highly recommended. Students are assumed to have a working knowledge of the Mac OS X or Microsoft Windows operating systems. The strategic goal of the course and book is to provide learners with an appreciation for the role computation plays in solving engineering problems. MATLAB specific skills that students are expected to be proficient at are: write scripts to solve engineering problems including interpolation, numerical integration and regression analysis, plot graphs to visualize, analyze and present numerical data, and publish reports.
"A Brief Introduction to Engineering Computation with MATLAB is specifically designed for students with no programming experience. However, students are expected to be proficient in First Year Mathematics and Sciences and access to good reference books are highly recommended. Students are assumed to have a working knowledge of the Mac OS X or Microsoft Windows operating systems. The strategic goal of the course and book is to provide learners with an appreciation for the role computation plays in solving engineering problems. MATLAB specific skills that students are expected to be proficient at are: write scripts to solve engineering problems including interpolation, numerical integration and regression analysis, plot graphs to visualize, analyze and present numerical data, and publish reports."--BC Campus website.
This eBook was written as the sequel to the eBook titled DC Circuits, which was written in 2016 by Chad Davis. This eBook covers Alternating Current (AC) circuit theory as well as a brief introduction of electronics. It is broken up into seven modules. Module 1 covers the basic theory of AC signals. Since only DC sources are used in the first eBook, details of AC signals such as sinusoidal waveforms (or sine waves), square waves, and triangle waves are provided. Module 2, titled AC Circuits Math Background, covers the mathematics background needed for solving AC circuit problems. The background material in Modules 1 and 2 are combined in Module 3 to solve circuits with AC sources that include resistors, inductors, and capacitors (RLC circuits).
Active Calculus is different from most existing calculus texts in at least the following ways: the text is freely readable online in HTML format and is also available for in PDF; in the electronic format, graphics are in full color and there are live links to java applets; version 2.0 now contains WeBWorK exercises in each chapter, which are fully interactive in the HTML format and included in print in the PDF; the text is open source, and interested users can gain access to the original source files on GitHub; the style of the text requires students to be active learners — there are very few worked examples in the text, with there instead being 3-4 activities per section that engage students in connecting ideas, solving problems, and developing understanding of key calculus concepts; each section begins with motivating questions, a brief introduction, and a preview activity, all of which are designed to be read and completed prior to class; following the WeBWorK exercises in each section, there are several challenging problems that require students to connect key ideas and write to communicate their understanding.
Active Calculus Multivariable is the continuation of Active Calculus to multivariable functions. The Active Calculus texts are different from most existing calculus texts in at least the following ways: the texts are free for download by students and instructors in .pdf format; in the electronic format, graphics are in full color and there are live html links to java applets; the texts are open source, and interested instructors can gain access to the original source files upon request; the style of the texts requires students to be active learners — there are very few worked examples in the texts, with there instead being 3-4 activities per section that engage students in connecting ideas, solving problems, and developing understanding of key calculus concepts; each section begins with motivating questions, a brief introduction, and a preview activity, all of which are designed to be read and completed prior to class; the exercises are few in number and challenging in nature.
Are you a current or future caregiver, or, a nurse or other healthcare professional who wants to learn more about Alzheimer’s disease? Here are the key content areas that will be addressed over 5 modules: Over 5 million Americans and an estimated 24 million people worldwide are living with Alzheimer’s disease (AD). Given the exponential aging of the population, these numbers are expected to increase dramatically over the next few decades; Alzheimer’s disease is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills and, eventually, the ability to carry out the simplest tasks. It is the most common cause of dementia among older adults and has both genetic and environmental factors in its development; AD is characterized by a variety of cognitive symptoms, including short-term memory loss, problems with problem-solving, judgment and recognition. There are also changes in mood and neuropsychiatric symptoms such as depression, hallucinations and paranoia. Behavioral expressions, include irritability, agitation, resistance to care, and wandering. In the later stages, the person is dependent in all activities of daily living and requires total care; There is no known cause, effective treatment or cure, but there are currently two classes of medications approved to enhance cognitive function, as well as, lifestyle-based preventive strategies thought to possibly reduce risk; There are evidence-based therapeutic approaches and communication strategies to enhance interactions and optimally, prevent behavioral expressions; The key principles of care for the hospitalized person with Alzheimer’s disease are examined, including the importance of therapeutic communication strategies to prevent behavioral expressions and other complications such as delirium and falls; Lastly, the essential role of the dementia caregiver is discussed, including potential consequences, stresses and gratifications, as well as the resources available.
This textbook, or really a “coursebook” for a college freshman-level class, has been updated for Spring 2014 and provides an introduction to programming and problem solving using both Matlab and Mathcad. We provide a balanced selection of introductory exercises and real-world problems (i.e. no “contrived” problems). We include many examples and screenshots to guide the reader. We assume no prior knowledge of Matlab or Mathcad.
As currently taught in the United States, introductory courses in analytical chemistry emphasize quantitative (and sometimes qualitative) methods of analysis along with a heavy dose of equilibrium chemistry. Analytical chemistry, however, is much more than a collection of analytical methods and an understanding of equilibrium chemistry; it is an approach to solving chemical problems. Although equilibrium chemistry and analytical methods are important, their coverage should not come at the expense of other equally important topics. The introductory course in analytical chemistry is the ideal place in the undergraduate chemistry curriculum for exploring topics such as experimental design, sampling, calibration strategies, standardization, optimization, statistics, and the validation of experimental results. Analytical methods come and go, but best practices for designing and validating analytical methods are universal. Because chemistry is an experimental science it is essential that all chemistry students understand the importance of making good measurements. My goal in preparing this textbook is to find a more appropriate balance between theory and practice, between “classical” and “modern” analytical methods, between analyzing samples and collecting samples and preparing them for analysis, and between analytical methods and data analysis. There is more material here than anyone can cover in one semester; it is my hope that the diversity of topics will meet the needs of different instructors, while, perhaps, suggesting some new topics to cover.
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.
Business Mathematics was written to meet the needs of a twenty-first century student. It takes a systematic approach to helping students learn how to think and centers on a structured process termed the PUPP Model (Plan, Understand, Perform, and Present). This process is found throughout the text and in every guided example to help students develop a step-by-step problem-solving approach. This textbook simplifies and integrates annuity types and variable calculations, utilizes relevant algebraic symbols, and is integrated with the Texas Instruments BAII+ calculator. It also contains structured exercises, annotated and detailed formulas, and relevant personal and professional applications in discussion, guided examples, case studies, and even homework questions.
Introduction to computer programming within a numerical computing environment (MATLAB or similar) including types of data representation, graphical display of data, and development of modular programs with application to engineering analysis and problem solving.
This CEO Report is about tapping into the psychological thought-processes of how great problem-solvers see, interpret and makes sense of being stuck with complexity and what they do (or fail to do) to progress. To uncover these underlying thinking patterns we administered a rigorous and systematic interview approach from clinical psychology called, Repertory Grid Technique (RGT). Our sample consists of fifty (50) seasoned CEOs /Executives spanning a wide range of industry sectors. Seven (7) inherent latent themes emerged from our analysis as to what are the core drivers (habits of mind) that help executives open up the alternatives whenever they find themselves stuck with complexity.
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.
The focus of this guided inquiry laboratory is to foster critical thinking that allows students to design, perform, and interpret experiments. In addition, the student acquires technical skills that are required for further advancement in experimental sciences. Although an ability to collect and analyze data in a quantitative manner is developed, the emphasis of the course is to provide a qualitative understanding of the basic concepts of chemistry. This is accomplished by demonstrating that chemical principles are derived from experimental data. The goal is to provide students both with a more accurate picture of the scientific process and with skills that are relevant to solving real life problems.
This first course in the physics curriculum introduces classical mechanics. Historically, a set of core concepts—space, time, mass, force, momentum, torque, and angular momentum—were introduced in classical mechanics in order to solve the most famous physics problem, the motion of the planets. The principles of mechanics successfully described many other phenomena encountered in the world. Conservation laws involving energy, momentum and angular momentum provided a second parallel approach to solving many of the same problems. In this course, we will investigate both approaches: Force and conservation laws. Our goal is to develop a conceptual understanding of the core concepts, a familiarity with the experimental verification of our theoretical laws, and an ability to apply the theoretical framework to describe and predict the motions of bodies.
Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza Collegein Cupertino, California. The textbook was developed over several years and has been used in regularand honors-level classroom settings and in distance learning classes. Courses using this textbook have beenarticulated by the University of California for transfer of credit. The textbook contains full materials forcourse offerings, including expository text, examples, labs, homework, and projects. A Teacher's Guide iscurrently available in print form and on the Connexions site at and supplemental course materials including additional problem sets and video lectures are available. The on-line text for each of these collections collections willmeet the Section 508 standards for accessibility. An on-line course based on the textbook was also developed by Illowsky and Dean. It has won an awardas the best on-line California community college course. The on-line course will be available at a later dateas a collection in Connexions, and each lesson in the on-line course will be linked to the on-line textbookchapter. The on-line course will include, in addition to expository text and examples, videos of courselectures in captioned and non-captioned format. The original preface to the book as written by professors Illowsky and Dean, now follows: This book is intended for introductory statistics courses being taken by students at two– and four–yearcolleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite.The book focuses on applications of statistical knowledge rather than the theory behind it. Thetext is named Collaborative Statistics because students learn best by doing. In fact, they learn best byworking in small groups. The old saying “two heads are better than one” truly applies here. Our emphasis in this text is on four main concepts: thinking statistically incorporating technology working collaboratively writing thoughtfully These concepts are integral to our course. Students learn the best by actively participating, not by justwatching and listening. Teaching should be highly interactive. Students need to be thoroughly engagedin the learning process in order to make sense of statistical concepts. Collaborative Statistics providestechniques for students to write across the curriculum, to collaborate with their peers, to think statistically,and to incorporate technology. This book takes students step by step. The text is interactive. Therefore, students can immediately applywhat they read. Once students have completed the process of problem solving, they can tackle interestingand challenging problems relevant to today's world. The problems require the students to apply theirnewly found skills. In addition, technology (TI-83 graphing calculators are highlighted) is incorporatedthroughout the text and the problems, as well as in the special group activities and projects. The book alsocontains labs that use real data and practices that lead students step by step through the problem solvingprocess. At De Anza, along with hundreds of other colleges across the country, the college audience involves alarge number of ESL students as well as students from many disciplines. The ESL students, as well asthe non-ESL students, have been especially appreciative of this text. They find it extremely readable andunderstandable. Collaborative Statistics has been used in classes that range from 20 to 120 students, and inregular, honor, and distance learning classes.
This College Algebra text will cover a combination of classical algebra and analytic geometry, with an introduction to the transcendental exponential and logarithmic functions. If mathematics is the language of science, then algebra is the grammar of that language. Like grammar, algebra provides a structure to mathematical notation, in addition to its uses in problem solving and its ability to change the appearance of an expression without changing the value.