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Applied Data Science for Data Analysts
by Kevin Coyle , Mark Roepke , Emma Freeman- 4.2
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Approx. 16 hours to complete
You'll work through the data science process to and use unsupervised learning to explore data, engineer and select meaningful features, and solve complex supervised learning problems using tree-based models. Feature Engineering and Selection Algorithm Selection and Decision Trees Label Imbalance and Sampling Grid Search for Hyperparameter Optimization Hyperparameter Search Lab Grid Search...
Atmospheric Chemistry: Planets and Life Beyond Earth
by Julia Lehman- 0.0
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Learn about the atmospheric chemistry of planets and celestial bodies and explore the possibility of finding life beyond Earth. Active and Passive exploration missions Cassini-Huygens Case Study The search for life on other planets The search for life beyond the solar system...
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Search Advertising
by Chris J. Vargo , Harsha Gangadharbatla- 4.4
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Approx. 10 hours to complete
Consumers search for virtually everything. This course shows small businesses how to create and execute search campaigns on Google Ads Search (formally AdWords). Beyond Google materials, practical campaign creation and optimization best practices and exercises are provided by real experts. Plan a search campaign, including: setting economic goals, defining targeting parameters, and aligning a campaign with business goals...
Strategies for Converting and Retaining Customers Online
by Stephane Muller- 4.7
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Approx. 11 hours to complete
Welcome to Course 2 of the E-Marketing Specialization: Strategies for Converting and Retaining Customers Online. - Explore how to leverage keywords and search engine marketing in your ad campaigns Introduction to Search Engine Marketing Pay-Per-Click (PPC) and Search Engine Optimization (SEO) Explore how to leverage keywords and search engine marketing in your ad campaigns...
Introduction to Systematic Review and Meta-Analysis
by Tianjing Li, MD, MHS, PHD , Kay Dickersin, PhD- 4.8
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Approx. 14 hours to complete
We will cover how to formulate an answerable research question, define inclusion and exclusion criteria, search for the evidence, extract data, assess the risk of bias in clinical trials, and perform a meta-analysis. Lecture 3D: Documenting Your Search and Conclusions Lecture 4A: Why Bias in the Individual Study is Important to a Systematic Review and Meta-Analysis...
Algorithms, Part I
by Kevin Wayne , Robert Sedgewick- 4.9
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Approx. 54 hours to complete
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. Stacks and Queues Stack and Queue Applications (optional)...
Recruiting, Hiring, and Onboarding Employees
by Amy Simon , Stacy Doepner-Hove- 4.7
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Approx. 20 hours to complete
It seems we are all competing for the best and brightest workers. This course is an introduction into the topic of recruitment, selection and onboarding. Aligning Recruitment and Selection with Company Strategy 3 A Systems View of Recruitment and Selection Aligning Recruitment and Selection with Company Strategy 4 Recruitment and Selection Summary Selection Methods and Tests...
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Algorithms for Searching, Sorting, and Indexing
by Sriram Sankaranarayanan- 4.6
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Approx. 34 hours to complete
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform....
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
by Tim Roughgarden- 4.8
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Approx. 17 hours to complete
The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts). Why Study Algorithms? Big Omega and Theta Welcome and Week 1 Overview Overview, Resources, and Policies...
Algorithms, Part II
by Robert Sedgewick , Kevin Wayne- 4.9
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Approx. 63 hours to complete
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. Depth-First Search Breadth-First Search Search Problems...
