Time Management
This course will teach you how to set specific goals and prioritize your tasks. You'll also learn various methods for setting priorities and increasing your productivity. Eventually, you’ll see that being busy isn’t the same as being effective.
Advanced Process Control
Comprehensive exploration of advanced process control techniques, covering linearization, modeling, stability analysis, stochastic processes, and control design methods for complex industrial systems.
Business Analytics for Management Decision
This course will be exclusively quantitative and an application to business/management-related problems. It is connected with problem sets and real life cases to know the relevance of a particular problem and the decision-making thereof.
Distributed Systems
These videos form an 8-lecture series on distributed systems, given as part of the undergraduate computer science course at the University of Cambridge.
SPSS Tutorial for Data Analysis - SPSS for Beginners
Comprehensive SPSS tutorial covering various statistical analyses, from basic tests to advanced regression techniques. Ideal for beginners seeking practical data analysis skills using IBM SPSS Statistics.
Financial Risk Management Training
Comprehensive financial risk management training covering key concepts, strategies, and practical applications through case studies. Learn to develop frameworks, manage people, and assess processes effectively.
SPSS
Learn essential statistical tests and analyses using SPSS, including Chi-Square, ANOVA, regression, and survival analysis, with practical examples and beginner-friendly tutorials.
Quantitative Social Science Methods
First course for incoming Harvard Government Department PhD students; also taken by students in other departments, and students elsewhere through the Harvard Extension School. Instructor: Gary King.
Probability and Random Processes
Explore random variables, probability distributions, and stochastic processes through intuitive explanations and practical applications in parameter estimation and noisy measurements.
Sports Analytics
Explore sports analytics through diverse projects, data scraping, and statistical analyses. Learn to predict outcomes, simulate games, and gain insights into various sports using data science techniques.
Biostatistics and Design of Experiments
The course encompasses topics such as distribution of data, sample size, tests of significance, data reduction, regression analysis, comparison of performance of drugs in clinical trials, design of experiments, screening and second order designs.
Singular Value Decomposition
Comprehensive exploration of Singular Value Decomposition, covering mathematical foundations, applications in data processing, and implementation in MATLAB and Python for various real-world scenarios.
Computational Systems Biology
Explore computational approaches to model and analyze biological systems, from network biology to dynamic modeling, with hands-on labs using MATLAB and other tools.
Kalman Filter for Beginners - Recursive Filters & MATLAB Examples
Explore recursive filters, including average, moving average, and low-pass filters, with practical MATLAB examples. Learn the foundations of Kalman filtering for enhanced estimation and data analysis skills.
Why Brain Science Needs an Edit - Mu-ming Poo - Radcliffe Institute
Explore gene editing in neuroscience, focusing on macaque monkey models for studying self-consciousness. Delve into ethical considerations of primate research and potential applications in brain disease treatments.
Working with SPSS
Learn to use SPSS for data analysis: from data entry and import to advanced statistical techniques like ANOVA, regression, and correlation. Master creating charts and formatting outputs.
Probability and Random Variables
Comprehensive exploration of probability theory and random variables, covering axioms, distributions, expectations, and advanced concepts for a solid foundation in statistical analysis.
Introduction to Biostatistics
In this course, we will discuss different statistical tools required to (i) analyze our observations, (ii) design new experiments, and (iii) integrate a large number of observations in a single unified model.
R Programming for Beginners - Learn R in 3 Hours
Comprehensive introduction to R programming, covering data types, manipulation, visualization, and neural networks. Includes hands-on examples and a Pokemon case study for practical application.
CBSE's Most Wanted 2020
Comprehensive preparation for CBSE/ISC 12th grade mathematics, covering key topics with practice questions, notes, and exam strategies for high scores.
Machine Translation
Explore AI-powered language translation, from statistical models to neural networks. Learn about RNNs, LSTMs, and sequence-to-sequence models, with a practical English-to-French translation example.