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Probability and Statistics II: Random Variables – Great Expectations to Bell Curves
by David Goldsman- 0.0
4 Weeks
This course discusses properties and applications of random variables. For instance, how many customers are likely to arrive in the next hour? This course discusses properties and applications of random variables. Such functions have many uses, including some wonderful applications in computer simulations. • Understand functions of random variables, and how they can be used in computer simulation applications....
$199
R Programming - Data Science using R
by Data Training Campus- 4.1
7 hours on-demand video
Anyone interested in R Programming related Training People interested in statistics and data sciences Basic knowledge of statistics Statistics Essentials for Analytics – Beginners: Data and analytics is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making. Module1: Introduction to basic elements of Statistics Market Basket Analysis in R:...
$11.99
Julia Scientific Programming
by Juan H Klopper , Henri Laurie- 4.5
Approx. 18 hours to complete
This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more. - Work in Jupyter notebooks using the Julia language Variables in Julia Functions in Julia Multiple Dispatch in Julia Approach to assessment in course Arithmetical and logical expressions in Julia Types and Arrays in Julia...
Data Analysis for Social Scientists
by Esther Duflo , Sara Fisher Ellison- 0.0
11 Weeks
MicroMasters in Statistics and Data Science (SDS). To pursue the SDS MicoMasters credential, pass this course, and enroll in and pass the final assessment at14. 310Fx Data Analysis in Social Sciences-Assessment on EdX. Complete all 4 courses and the capstone exam in the SDS program to accelerate your path towards graduate studies at MIT or other universities....
Algorithms for Searching, Sorting, and Indexing
by Sriram Sankaranarayanan- 4.6
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....
Machine Learning with Python: from Linear Models to Deep Learning
by Regina Barzilay , Tommi Jaakkola , Karene Chu- 0.0
15 Weeks
-- Part of the MITx MicroMasters program in Statistics and Data Science. Students will implement and experiment with the algorithms in several Python projects designed for different practical applications. This course is part of theMITx MicroMasters Program in Statistics and Data Science. Choose suitable models for different applications...
$300
Probability and Statistics III: A Gentle Introduction to Statistics
by David Goldsman- 0.0
4 Weeks
We then discuss elementary descriptive statistics and estimation methods, including unbiased estimation, maximum likelihood estimation, and the method of moments – you gotta love your MoM! Finally, we describe the t, χ2, and F sampling distributions, which will prove to be useful in upcoming statistical applications. Recognize elementary methods of descriptive statistics...
$199
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Financial Engineering and Risk Management Part II
by Martin Haugh , Garud Iyengar- 4.7
Approx. 17 hours to complete
The emphasis of FE & RM Part II will be on the use of simple stochastic models to (i) solve portfolio optimization problems (ii) price derivative securities in various asset classes including equities and credit and (iii) consider some advanced applications of financial engineering including algorithmic trading and the pricing of real options....
Probability and Statistics III: A Gentle Introduction to Statistics
by David Goldsman- 0.0
4 Weeks
We then discuss elementary descriptive statistics and estimation methods, including unbiased estimation, maximum likelihood estimation, and the method of moments – you gotta love your MoM! Finally, we describe the t, X2, and F sampling distributions, which will prove to be useful in upcoming statistical applications. Recognize elementary methods of descriptive statistics...
$199
Data Analysis for Social Scientists
by Esther Duflo , Sara Fisher Ellison- 0.0
11 Weeks
MicroMasters in Statistics and Data Science (SDS). To pursue the SDS MicoMasters credential, pass this course, and enroll in and pass the final assessment at14. 310Fx Data Analysis in Social Sciences-Assessment on EdX. Complete all 4 courses and the capstone exam in the SDS program to accelerate your path towards graduate studies at MIT or other universities....