Calculus One by The Ohio State University

<div dir="ltr" style="text-align: left;" trbidi="on"><div><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjiLzggat4VT4jYBk50bH9YPwxrjWgJA8HoRvPQY3tYgxcnjQqrn979_Mfg_9STFun5YYOEJCAzGqX9UySNQFtRNViQKskmJxk1rO-zh3WODZwMTEgBo8wL6rAFMWhMUMhWbCTwtJoCU32e/s1600/OSU-coursera-squareFront+%25281%2529.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjiLzggat4VT4jYBk50bH9YPwxrjWgJA8HoRvPQY3tYgxcnjQqrn979_Mfg_9STFun5YYOEJCAzGqX9UySNQFtRNViQKskmJxk1rO-zh3WODZwMTEgBo8wL6rAFMWhMUMhWbCTwtJoCU32e/s400/OSU-coursera-squareFront+%25281%2529.png" /></a></div><div><br /></div><div><a href="https://www.coursera.org/learn/calculus1">Program Information</a> </div><div><b><br /></b></div><div><b>About this course:</b> </div><div>Calculus is about the very large, the very small, and how things change. The surprise is that something seemingly so abstract ends up explaining the real world. Calculus plays a starring role in the biological, physical, and social sciences. By focusing outside of the classroom, we will see examples of calculus appearing in daily life. This course is a first and friendly introduction to calculus, suitable for someone who has never seen the subject before, or for someone who has seen some calculus but wants to review the concepts and practice applying those concepts to solve problems.</div></div>

Calculus One by The Ohio State University

Program Information   About this course:   Calculus is about the very large, the very small, and how things change. The surprise is that som...

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Algorithms: Design and Analysis, Part 1

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgSBI0ero3Qhr9QLDBtTrP9k93yt80PmOv7cIM-kga_lAVyPWtj_RCaWhKQe-PsIXzKZkLemq8NSbxgyl4mMoE-TNu3YhikCbFuC-GdS4-OdEPqDaKYQoUXI4KYotNNq88Pmt_y19FGtbIh/s1600/Coursera-SUSig_StnfrdUStack_SQ.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgSBI0ero3Qhr9QLDBtTrP9k93yt80PmOv7cIM-kga_lAVyPWtj_RCaWhKQe-PsIXzKZkLemq8NSbxgyl4mMoE-TNu3YhikCbFuC-GdS4-OdEPqDaKYQoUXI4KYotNNq88Pmt_y19FGtbIh/s400/Coursera-SUSig_StnfrdUStack_SQ.png" /></a><br /><br /><a href="https://www.coursera.org/learn/algorithm-design-analysis">Program Information</a><br /><br /><div class="about-section-wrapper" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 30px;"><div class="rc-TogglableContent about-section" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1.0" style="box-sizing: border-box;"><div class="content" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1.0.0" style="box-sizing: border-box; height: auto; position: relative;"><div class="content-inner" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0" style="box-sizing: border-box;"><div class="body-1-text course-description" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0" style="box-sizing: border-box; margin-bottom: 10px; white-space: pre-wrap;"><strong class="body-2-text" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.0" style="box-sizing: border-box;">About this course: </strong><span data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.1" style="box-sizing: border-box;">Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This course is an introduction to algorithms for learners with at least a little programming experience. The course is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this course, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists. Specific topics include: "Big-oh" notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), randomized algorithms (QuickSort, contraction algorithm for min cuts), data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of BFS and DFS, connectivity, shortest paths). About the instructor: Tim Roughgarden has been a professor in the Computer Science Department at Stanford University since 2004. He has taught and published extensively on the subject of algorithms and their applications.</span></div></div></div><div class="toggle-button-wrapper" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.1.0.1" style="box-sizing: border-box; margin-top: 5px;"><br /></div></div></div><div class="target-audience-section" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.2" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 30px; margin-top: 20px;"><div class="body-1-text course-description" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.2.0" style="box-sizing: border-box; margin-bottom: 10px;"><strong class="body-2-text" data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.2.0.0" style="box-sizing: border-box;">Who is this class for: </strong><span data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.2.0.1" style="box-sizing: border-box;">Learners with at least a little bit of programming experience who want to learn the essentials of algorithms. In a University computer science curriculum, this course is typically taken in the third year.</span></div><div><span data-reactid=".2276bjcxudc.0.0.1.1.0.0.0:$section_overview.1.2.0.1" style="box-sizing: border-box;"><br /></span></div></div></div>

Algorithms: Design and Analysis, Part 1

Program Information About this course: Algorithms are the heart of computer science, and the subject has countless practical applications as...

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Make Strategic Financial Decisions: Specialization by Michgan

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfGIhOpVHlwIyCxP84-oFUMQJH7DTWbU43yhyV7SzPCeqv6HBYFfVPU-TzY0ODfhbECRgzcYQgCVrxW9NALBqmeEwslTMd_cVC-8ABZj3X3FhMQpODNL2Q926niTiPiiqIISMHWwyDgj3s/s1600/U-M_LogoSmHoriz_200x48.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfGIhOpVHlwIyCxP84-oFUMQJH7DTWbU43yhyV7SzPCeqv6HBYFfVPU-TzY0ODfhbECRgzcYQgCVrxW9NALBqmeEwslTMd_cVC-8ABZj3X3FhMQpODNL2Q926niTiPiiqIISMHWwyDgj3s/s400/U-M_LogoSmHoriz_200x48.png" /></a><br /><br /><a href="https://www.coursera.org/specializations/valuation-investment">Program Information</a><br /><br /><h1 style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans-Light, Arial, sans-serif; font-size: 32px; font-weight: normal; line-height: 36px; margin: 0px 0px 20px; padding: 0px;">Evaluate risk and reward, assess alternatives, and determine the value of a project or company.</h1><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; min-height: 20px;">This Specialization builds on the success of the Introduction to Finance course and provides a rigorous introduction to core topics in financial valuation, including time value of money, cash flow analysis, asset pricing, and risk and return. In the final Capstone Project, you’ll apply your skills to research, analyze, and value a real-world enterprise.</div><div style="background-color: whitesmoke; box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; min-height: 20px;"><br /></div><div class="partner-marketing-blurb" data-reactid=".0.0.1.1.1.1.3.1:$3.0.1.0" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 16px; line-height: 19px;">Michigan’s academic vigor offers excellence across disciplines and around the globe. The University is recognized as a leader in higher education due to the outstanding quality of its 19 schools and colleges, internationally recognized faculty, and departments with 250 degree programs.</div><div class="partner-short-description" data-reactid=".0.0.1.1.1.1.3.1:$3.0.1.1" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 14px; line-height: 19px; padding-top: 25px;">The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.</div></div>

Make Strategic Financial Decisions: Specialization by Michgan

Program Information Evaluate risk and reward, assess alternatives, and determine the value of a project or company. This Specialization buil...

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Cryptography I

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1zT5yvKdyTFGpJW1r662OShTZvNnLNtTDxoW7SkAqwj57slblgNORyDb2Tk8VhFWGGrgU9zyGwadZMa85nrSCHjvtD7assQpLsdpT9aN9n92ZY5gAX_c4ZkhD7OnWvF3L3Ih7RQ1PDULd/s1600/Coursera-SUSig_StnfrdUStack_SQ.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1zT5yvKdyTFGpJW1r662OShTZvNnLNtTDxoW7SkAqwj57slblgNORyDb2Tk8VhFWGGrgU9zyGwadZMa85nrSCHjvtD7assQpLsdpT9aN9n92ZY5gAX_c4ZkhD7OnWvF3L3Ih7RQ1PDULd/s400/Coursera-SUSig_StnfrdUStack_SQ.png" /></a><br /><br /><a href="https://www.coursera.org/learn/crypto">Program Information</a><br /><br /><strong class="body-2-text" data-reactid=".sdr5rgj2m8.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.0" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; white-space: pre-wrap;">About this course: </strong><span data-reactid=".sdr5rgj2m8.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.1" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; white-space: pre-wrap;">Cryptography is an indispensable tool for protecting information in computer systems. In this course you will learn the inner workings of cryptographic systems and how to correctly use them in real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic. We will examine many deployed protocols and analyze mistakes in existing systems. The second half of the course discusses public-key techniques that let two parties generate a shared secret key. Throughout the course participants will be exposed to many exciting open problems in the field and work on fun (optional) programming projects. In a second course (Crypto II) we will cover more advanced cryptographic tasks such as zero-knowledge, privacy mechanisms, and other forms of encryption.</span></div>

Cryptography I

Program Information About this course: Cryptography is an indispensable tool for protecting information in computer systems. In this course ...

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Journey to the Frontier of Computational Biology

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgmzASbfy8U22Ykm4tkyUmFNdKTN2Z31robaQbKNGCF1cwWPiarjU1IWLXP31LDuuEvhF_i3omJbvz5wVgJTlilsFbaWQyLkLeELeYwfQ4FHHpPg6aNr5nyCT7c4PgOot2_8FB1Ly6Az5ir/s1600/UCSanDiego-Coursera-wide+%25281%2529.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgmzASbfy8U22Ykm4tkyUmFNdKTN2Z31robaQbKNGCF1cwWPiarjU1IWLXP31LDuuEvhF_i3omJbvz5wVgJTlilsFbaWQyLkLeELeYwfQ4FHHpPg6aNr5nyCT7c4PgOot2_8FB1Ly6Az5ir/s400/UCSanDiego-Coursera-wide+%25281%2529.png" /></a><br /><br /><br /><a href="https://www.coursera.org/specializations/computational-biology">Program Information</a><br /><h2 style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 22px; font-weight: normal; line-height: 24px; margin: 36px 0px 16px; padding: 0px;">Join Us in a Top 50 MOOC of All Time!</h2><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 20px; min-height: 20px;">How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth?</div><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 20px; min-height: 20px;">When you complete this Specialization, you will learn how to answer many questions in modern biology that have become inseparable from the computational approaches used to solve them. You will also obtain a toolkit of existing software resources built on these computational approaches and that are used by thousands of biologists every day in one of the fastest growing fields in science.</div><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 20px; min-height: 20px;">Although this Specialization centers on computational topics, you do not need to know how to program in order to complete it. If you are interested in programming, we feature an "Honors Track" (called "hacker track" in previous runs of the course). The Honors Track allows you to implement the bioinformatics algorithms that you will encounter along the way in dozens of automatically graded coding challenges. By completing the Honors Track, you will be a bioinformatics software professional!</div><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 20px; min-height: 20px;">Learn more about the Bioinformatics Specialization (including why we are wearing these crazy outfits) by watching our <a href="https://youtu.be/yfXeKPt0nw4" rel="noopener nofollow" style="background: transparent; box-sizing: border-box; color: #428bca; margin-bottom: 0px !important; text-decoration: none;" target="_blank">introductory video</a>.</div><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 20px; min-height: 20px;">You can purchase the Specialization's print companion, <em style="box-sizing: border-box;">Bioinformatics Algorithms: An Active Learning Approach</em>, from the <a href="http://bioinformaticsalgorithms.com/" rel="noopener nofollow" style="background: transparent; box-sizing: border-box; color: #428bca; margin-bottom: 0px !important; text-decoration: none;" target="_blank">textbook website</a>.</div><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; min-height: 20px;">Our first course, "Finding Hidden Messages in DNA", was named a top-50 MOOC of all time by <a href="https://www.class-central.com/report/top-moocs/" rel="noopener nofollow" style="background: transparent; box-sizing: border-box; color: #428bca; margin-bottom: 0px !important; text-decoration: none;" target="_blank">Class Central</a>!</div></div>

Journey to the Frontier of Computational Biology

Program Information Join Us in a Top 50 MOOC of All Time! How do we sequence and compare genomes? How do we identify the genetic basis for d...

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Computational Neuroscience - Washington University

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQkytVSituCC6dHv3OXDE37PLoQOI4_i0uateqaSIvLc2tsnXQNDWkVBqZD_lcLHniKlYIeumxvJ0OS35nUVpNMNxnt8ic9givXjSWP8gFcmK60pmBtBiSDR6Ym12-XvWAKHakGT3PfANo/s1600/UW_square_180x180.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQkytVSituCC6dHv3OXDE37PLoQOI4_i0uateqaSIvLc2tsnXQNDWkVBqZD_lcLHniKlYIeumxvJ0OS35nUVpNMNxnt8ic9givXjSWP8gFcmK60pmBtBiSDR6Ym12-XvWAKHakGT3PfANo/s400/UW_square_180x180.png" /></a><br /><br /><a href="https://www.coursera.org/learn/computational-neurosciencecompneuro">Program Information</a><br /><br /><strong class="body-2-text" data-reactid=".s1lfym5w5c.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.0" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; white-space: pre-wrap;">About this course: </strong><span data-reactid=".s1lfym5w5c.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.1" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; white-space: pre-wrap;">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 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.</span><br /><span data-reactid=".s1lfym5w5c.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.1" style="background-color: white; box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; white-space: pre-wrap;"><br /></span><div class="headline-2-text partner-name" data-reactid=".s1lfym5w5c.0.0.1.1.0.0.0:$section_creators.1.0.0" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 20px; line-height: 24px; margin-bottom: 15px;"><span style="background-color: white;">About University of Washington</span></div><span data-reactid=".s1lfym5w5c.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.1" style="background-color: white; box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; white-space: pre-wrap;"></span><br /><div class="body-1-text" data-reactid=".s1lfym5w5c.0.0.1.1.0.0.0:$section_creators.1.0.1" style="box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px;"><span style="background-color: white;">Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.</span></div></div>

Computational Neuroscience - Washington University

Program Information About this course: This course provides an introduction to basic computational methods for understanding what nervous sy...

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Expertise for Professionals and Students in Biotechnology and Biomedical Data Sciences

<div dir="ltr" style="text-align: left;" trbidi="on"><br /><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiwtCPXOu0JnmuvmSGJi6gMGyv-ztxoNBJ0ejcqOT75w3TsvVm-lAu1WOe3f7RKPRb8vGm6WU1aQ9X8RtEUufg-Ojvv97QL-3FuolCUl0H7PE8VBJNjbVjTS0weUILgKc-sihz20BGVRHA0/s1600/wide_logo_200X48_v2.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiwtCPXOu0JnmuvmSGJi6gMGyv-ztxoNBJ0ejcqOT75w3TsvVm-lAu1WOe3f7RKPRb8vGm6WU1aQ9X8RtEUufg-Ojvv97QL-3FuolCUl0H7PE8VBJNjbVjTS0weUILgKc-sihz20BGVRHA0/s400/wide_logo_200X48_v2.png" /></a><br /><br /><a href="https://www.coursera.org/specializations/systems-biology">Program Information</a><br /><br /><h1 style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans-Light, Arial, sans-serif; font-size: 32px; font-weight: normal; line-height: 36px; margin: 0px 0px 20px; padding: 0px;">Design systems-level experiments using appropriate cutting edge techniques, collect big data, and analyze and interpret small and big data sets quantitatively.</h1><div style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; min-height: 20px;">The Systems Biology Specialization covers the concepts and methodologies used in systems-level analysis of biomedical systems. Successful participants will learn how to use experimental, computational and mathematical methods in systems biology and how to design practical systems-level frameworks to address questions in a variety of biomedical fields. In the final Capstone Project, students will apply the methods they learned in five courses of specialization to work on a research project.</div><div style="background-color: whitesmoke; box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; min-height: 20px;"><br /></div><div class="partner-marketing-blurb" data-reactid=".0.0.1.1.1.1.3.1:$27.0.1.0" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 16px; line-height: 19px;">Icahn School of Medicine at Mount Sinai, in New York City, is a leader in medical and scientific training and education, biomedical research and patient care. The Institute for Systems Biomedicine is an interdisciplinary entity that brings together faculty who are world leaders in systems biology, medicine and systems pharmacology research at Mount Sinai.</div><div class="partner-short-description" data-reactid=".0.0.1.1.1.1.3.1:$27.0.1.1" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 14px; line-height: 19px; padding-top: 25px;">The Icahn School of Medicine at Mount Sinai, in New York City is a leader in medical and scientific training and education, biomedical research and patient care.</div></div>

Expertise for Professionals and Students in Biotechnology and Biomedical Data Sciences

Program Information Design systems-level experiments using appropriate cutting edge techniques, collect big data, and analyze and interpret ...

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An Introduction to Consumer Neuroscience & Neuromarketing

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi62ARe-2xuBRCYlOzvb2f18Yx6nVFCMcRnzfY72yAnEeUH-jyZ_SCBWnOu_sA4-mz27oUzUSRMgexJ_78PinrALRt-mzjYV6Hc2Q5X2-KjjS5Rk-BpwpbHn9gvVgTwj66ELy53GnGBl8Fn/s1600/cbs-coursera-logo-square__1280x1280px.png" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="200" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi62ARe-2xuBRCYlOzvb2f18Yx6nVFCMcRnzfY72yAnEeUH-jyZ_SCBWnOu_sA4-mz27oUzUSRMgexJ_78PinrALRt-mzjYV6Hc2Q5X2-KjjS5Rk-BpwpbHn9gvVgTwj66ELy53GnGBl8Fn/s200/cbs-coursera-logo-square__1280x1280px.png" width="200" /></a><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><a href="https://www.coursera.org/learn/neuromarketing">Program Information</a><br /><br /><div class="content" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.1.0.0" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; height: auto; line-height: 21px; position: relative;"><div class="content-inner" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0" style="box-sizing: border-box;"><div class="body-1-text course-description" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0" style="box-sizing: border-box; margin-bottom: 10px; white-space: pre-wrap;"><strong class="body-2-text" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.0" style="box-sizing: border-box;">About this course: </strong><span data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.1" style="box-sizing: border-box;">How do we make decisions as consumers? What do we pay attention to, and how do our initial responses predict our final choices? To what extent are these processes unconscious and cannot be reflected in overt reports? This course will provide you with an introduction to some of the most basic methods in the emerging fields of consumer neuroscience and neuromarketing. You will learn about the methods employed and what they mean. You will learn about the basic brain mechanisms in consumer choice, and how to stay updated on these topics. The course will give an overview of the current and future uses of neuroscience in business.</span></div><div><span data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.1.0.0.0.0.1" style="box-sizing: border-box;"><table class="basic-info-table bt3-table bt3-table-striped bt3-table-bordered bt3-table-responsive" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0" style="border-collapse: collapse; border-spacing: 0px; border: 1px solid rgb(221, 221, 221); box-sizing: border-box; color: #333333; font-size: 14px; line-height: 21px; margin-bottom: 20px; max-width: 100%; width: 700px;"><tbody data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0" style="box-sizing: border-box;"><tr data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.1" style="box-sizing: border-box;"><td data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.1.0" style="background-color: #f9f9f9; border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; min-width: 200px; padding: 15px 20px; vertical-align: top; width: 200px;"><span class="td-title" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.1.0.1" style="box-sizing: border-box; font-weight: bold; vertical-align: top;">Level</span></td><td class="td-data" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.1.1" style="background-color: #f9f9f9; border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; padding: 15px 20px; vertical-align: middle;">Beginner</td></tr><tr data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.3" style="box-sizing: border-box;"><td data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.3.0" style="border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; min-width: 200px; padding: 15px 20px; vertical-align: top; width: 200px;"><span class="cif-language" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.3.0.0" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; font-size: 20px; line-height: 1; margin-left: 5px; margin-right: 20px; speak: none;"></span><span class="td-title" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.3.0.1" style="box-sizing: border-box; font-weight: bold; vertical-align: top;">Language</span></td><td class="td-data" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.3.1" style="border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; padding: 15px 20px; vertical-align: middle;"><span data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.3.1.0" style="box-sizing: border-box;">English</span></td></tr><tr data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.5" style="box-sizing: border-box;"><td data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.5.0" style="background-color: #f9f9f9; border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; min-width: 200px; padding: 15px 20px; vertical-align: top; width: 200px;"><span class="cif-graduation-hat i-how-to-pass" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.5.0.0" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; font-size: 20px; line-height: 1; margin-left: 5px; margin-right: 10px; speak: none;"></span><span class="td-title" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.5.0.1" style="box-sizing: border-box; font-weight: bold; vertical-align: top;">How To Pass</span></td><td class="td-data" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.5.1" style="background-color: #f9f9f9; border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; padding: 15px 20px; vertical-align: middle;">Pass all graded assignments to complete the course.</td></tr><tr data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6" style="box-sizing: border-box;"><td data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.0" style="border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; min-width: 200px; padding: 15px 20px; vertical-align: top; width: 200px;"><span class="cif-star-o" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.0.0" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; font-size: 20px; line-height: 1; margin-left: 5px; margin-right: 20px; speak: none;"></span><span class="td-title" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.0.1" style="box-sizing: border-box; font-weight: bold; vertical-align: top;">User Ratings</span></td><td class="td-data" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1" style="border: 1px solid rgb(221, 221, 221); box-sizing: border-box; line-height: 1.42857; padding: 15px 20px; vertical-align: middle;"><div class="ratings-info" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0" style="box-sizing: border-box;"><div class="rc-CourseRatingIcons small read-only" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.0" style="-webkit-box-align: center; align-items: center; box-sizing: border-box; cursor: default; display: inline-block; float: left; font-size: 18px; margin-right: 16px;"><span class="c-course-rating-icon cif-star" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.0.$1" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; line-height: 1; margin-right: 5px; speak: none;"></span><span class="c-course-rating-icon cif-star" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.0.$2" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; line-height: 1; margin-right: 5px; speak: none;"></span><span class="c-course-rating-icon cif-star" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.0.$3" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; line-height: 1; margin-right: 5px; speak: none;"></span><span class="c-course-rating-icon cif-star" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.0.$4" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; line-height: 1; margin-right: 5px; speak: none;"></span><span class="c-course-rating-icon cif-star" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.0.$5" style="-webkit-font-smoothing: antialiased; box-sizing: border-box; color: #d49261; display: inline-block; font-family: coursera-iconfont; line-height: 1; margin-right: 0px; speak: none;"></span></div><div class="ratings-text bt3-hidden-xs" data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.2" style="box-sizing: border-box; display: inline-block;"><span data-reactid=".5xty4s7nr4.0.0.1.1.0.0.0:$section_overview.1.6.0.0.6.1.0.2.0" style="box-sizing: border-box;">Average User Rating 5.0</span></div></div></td></tr></tbody></table></span></div></div></div></div>

An Introduction to Consumer Neuroscience & Neuromarketing

Program Information About this course: How do we make decisions as consumers? What do we pay attention to, and how do our initial responses ...

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Master Statistics with R: Duke University

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEionIIzqyZyZP3vSjBkU9PVcJYfKmvjFLYSLd8O-a_UCzoTkAJUtKm1CNrMXO9lOb0WnC0GvGcKqdqAZYB7oaBGgbP0g1lbL_JgHjI6zy7ITfwemJQcjeZ-ZBHC0UC3O9cggTMaojGMiYkv/s1600/dukewidelogo2.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEionIIzqyZyZP3vSjBkU9PVcJYfKmvjFLYSLd8O-a_UCzoTkAJUtKm1CNrMXO9lOb0WnC0GvGcKqdqAZYB7oaBGgbP0g1lbL_JgHjI6zy7ITfwemJQcjeZ-ZBHC0UC3O9cggTMaojGMiYkv/s400/dukewidelogo2.png" /></a><br /><br />Program: Paid<br /><a href="https://www.coursera.org/specializations/statistics">Program Information</a><br /><br /><div class="rc-SectionHeader" data-reactid=".0.0.1.1.1.1.0.0" style="background-color: whitesmoke; border-bottom-color: rgb(230, 230, 230); border-bottom-style: solid; border-bottom-width: 1px; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 20px;"><div class="s12n-section-header-title" data-reactid=".0.0.1.1.1.1.0.0.0" style="border-bottom-color: rgb(184, 145, 115); border-bottom-style: solid; border-bottom-width: 1px; box-sizing: border-box; display: inline-block; font-size: 16px; line-height: 19px; margin: 0px 0px -1px; padding: 10px 40px 10px 0px;">About This Specialization</div></div><div class="rc-CML styled" data-reactid=".0.0.1.1.1.1.0.1" style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; word-wrap: break-word;"><div data-reactid=".0.0.1.1.1.1.0.1.0" style="box-sizing: border-box; margin-bottom: 0px !important;"><div style="box-sizing: border-box; margin-bottom: 20px; min-height: 20px;">In this Specialization, you will learn to analyze and visualize data in R and created reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.</div><div style="box-sizing: border-box; min-height: 20px;">You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions.</div><div style="box-sizing: border-box; min-height: 20px;"><br /></div></div></div></div>

Master Statistics with R: Duke University

Program: Paid Program Information About This Specialization In this Specialization, you will learn to analyze and visualize data in R and cr...

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Data Science: Big Data Specialization: UC San Diego

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6davQOk2r_Fv8BtENJErvEadEuNifLnpANHuduz0S1hdSF4SqgD5krDVpV-NA89cBZQyrh8Ao4FHDErxnsUJhXcBBoHInu-PYgbdGlJOiIOe8LL1bUuSClgNvcKShnK2t5DJexyoFInqf/s1600/UCSanDiego-Coursera-wide.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6davQOk2r_Fv8BtENJErvEadEuNifLnpANHuduz0S1hdSF4SqgD5krDVpV-NA89cBZQyrh8Ao4FHDErxnsUJhXcBBoHInu-PYgbdGlJOiIOe8LL1bUuSClgNvcKShnK2t5DJexyoFInqf/s400/UCSanDiego-Coursera-wide.png" /></a><br /><br />Program fee: paid <br /><a href="https://www.coursera.org/specializations/bigdata">Program information</a><br /><br /><br /><div data-reactid=".0.0.1.1.1.1.0.2" style="-webkit-text-stroke-width: 0px; background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: 21px; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 1; word-spacing: 0px;"></div><br /><div class="rc-CML styled" data-reactid=".0.0.1.1.1.1.0.1" style="-webkit-text-stroke-width: 0px; background-color: whitesmoke; box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: 21px; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 1; word-spacing: 0px; word-wrap: break-word;"><div data-reactid=".0.0.1.1.1.1.0.1.0" style="box-sizing: border-box; margin-bottom: 0px !important;"><div style="box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 0px !important; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 20px;">Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.</div><div style="box-sizing: border-box; color: #333333; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; margin-bottom: 0px !important; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 20px;"><br /></div><div class="partner-marketing-blurb" data-reactid=".0.0.1.1.1.1.3.1:$53.0.1.0" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 16px; line-height: 19px;">The San Diego Supercomputer Center (SDSC) at UC San Diego is a leader in data-intensive computing and cyberinfrastructure. SDSC supports hundreds of multidisciplinary programs spanning domains from earth sciences and biology to astrophysics and bioinformatics.</div><div class="partner-short-description" data-reactid=".0.0.1.1.1.1.3.1:$53.0.1.1" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; line-height: 19px; padding-top: 25px;">UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.</div></div></div></div>

Data Science: Big Data Specialization: UC San Diego

Program fee: paid Program information Do you need to understand big data and how it will impact your business? This Specialization is for yo...

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Data Science Specilazation: Johns Hopkins University

<div dir="ltr" style="text-align: left;" trbidi="on"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj17xW8IWzun_qXETJv-na80ApUNrf2bshq-hTN6UaBLEkWUEY_g4jAYPDtgNbCb4vjw3pDCofIxe5mvVXTtDlYceZedK6QZWdaHxg7FJzcrcIrM2Ra37vVVKPsY7IPCtbhqtDIdF5WkBn5/s1600/JHU-Logo-Square-Mini_180px.png" imageanchor="1"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj17xW8IWzun_qXETJv-na80ApUNrf2bshq-hTN6UaBLEkWUEY_g4jAYPDtgNbCb4vjw3pDCofIxe5mvVXTtDlYceZedK6QZWdaHxg7FJzcrcIrM2Ra37vVVKPsY7IPCtbhqtDIdF5WkBn5/s400/JHU-Logo-Square-Mini_180px.png" /></a><br />Program fee: Paid  <br /><a href="https://www.coursera.org/specializations/jhu-data-science#">Program Information</a><br /><br /><h1 style="background-color: whitesmoke; box-sizing: border-box; color: #333333; font-family: OpenSans-Light, Arial, sans-serif; font-size: 32px; font-weight: normal; line-height: 36px; margin: 0px 0px 20px; padding: 0px;">Ask the right questions, manipulate data sets, and create visualizations to communicate results.</h1><div style="background-color: whitesmoke; box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; min-height: 20px;"><span style="color: #333333;">This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inference</span>s and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.</div><div style="background-color: whitesmoke; box-sizing: border-box; font-family: OpenSans, Arial, sans-serif; font-size: 14px; line-height: 21px; min-height: 20px;"><br /></div><div class="partner-marketing-blurb" data-reactid=".0.0.1.1.1.1.3.1:$8.0.1.0" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 16px; line-height: 19px;">Johns Hopkins University is recognized as a destination for excellent, ambitious scholars and a world leader in teaching and research. The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.</div><div class="partner-short-description" data-reactid=".0.0.1.1.1.1.3.1:$8.0.1.1" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 14px; line-height: 19px; padding-top: 25px;">The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.</div><div class="partner-short-description" data-reactid=".0.0.1.1.1.1.3.1:$8.0.1.1" style="box-sizing: border-box; font-family: OpenSans-Light, Arial, sans-serif; font-size: 14px; line-height: 19px; padding-top: 25px;"><br /></div><div class="partner-short-description" data-reactid=".0.0.1.1.1.1.3.1:$8.0.1.1" style="box-sizing: border-box; color: white; font-family: OpenSans-Light, Arial, sans-serif; font-size: 14px; line-height: 19px; padding-top: 25px;"><br /></div></div>

Data Science Specilazation: Johns Hopkins University

Program fee: Paid   Program Information Ask the right questions, manipulate data sets, and create visualizations to communicate results. Thi...

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