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Learn Analysis online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
5,997 courses
Harvard University
Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.
This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow;…
Instructor: Dennis Freeman, Kendra Pugh This course provides an integrated introduction to electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making. The lecture videos provide an overview of each topic, whi…
Harvard University
Build a foundation in R and learn how to wrangle, analyze, and visualize data.
Harvard University
Learn basic data visualization principles and how to apply them using ggplot2.
View the complete course: http://ocw.mit.edu/6-046JS15 Instructors: Erik Demaine, Srinivas Devadas, Nancy Ann Lynch 6.046 introduces students to the design of computer algorithms, as well as analysis of sophisticated algorithms. License: Creative Commons BY-NC-SA More information at http://ocw.mit.…
Harvard University
Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.
Princeton University
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…
Princeton University
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…
Harvard University
Show what you've learned from the Professional Certificate Program in Data Science.
IBM
This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own!
IIT Bombay
Computer Science and Engineering course by Prof. Varsha Apte.
Stanford Online
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).
Complex data can be represented as a graph of relationships between objects. Such networks are a fundamental tool for modeling social, technological, and biological systems. This course focuses on the computational, algorithmic, and modeling challenges specific to the analysis of massive graphs. By…
This course covers important research on the structure and analysis of such large social and information networks and on models and algorithms that abstract their basic properties. Students will explore how to practically analyze large-scale network data and how to reason about it through models fo…
Great Learning
This free Power BI training course equips you with the essential skills to import, prepare, analyze, and present data using Power BI. You’ll learn how to work in the Power BI environment, use Power BI Desktop, import data for analysis, and prepare data for reporting. The course also covers data mod…
Stanford Online
The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).
Harvard University
Learn inference and modeling, two of the most widely used statistical tools in data analysis.
