Statistics.com offers 110+ courses for
novices, experts, and those in between. Most courses are 4-weeks long and put
you in direct contact with leading experts and authors. Whether you want to
learn the fundamentals, polish your skills, master new methods or tackle new
cutting edge topics, we have a course for you.
Learn topics
in Data Science
Data analytics (data mining, predictive
modeling, forecasting, social network anaysis, text analytics)
Statistical programming (how to use R, Python,
SQL and Hadoop for analytics and statistical analysis)
Research
statistics
Biostatistics (controlled clinical trials,
epidemiology and environmental science)
Social science (statistical methods needed for
designing and analyzing studies - including Bayesian analysis, conducting
surveys and analyzing the data they yield, and a unique concentration strand
devoted to Rasch methods)
Introductory
Statistics
We, the Center for eLearning and Training
(C-eLT), Pune, partner with Statistics.com and offer these courses to Indian
participants at special prices payable in INR.
Let me tell you in very brief why prescribing
these courses for your personnel is such a great idea:
- The courses enable mastery over statistical skill sets and give your team a competitive edge
- They enhance your personnel’s ability to make smarter business decisions that are data driven
- They put professional growth on the fast track
- The participants have the opportunity to learn from top statisticians who are authors of popular books on Statistics and often professors at leading universities.
- The courses are online and participants can follow a flexible schedule in terms of time and space
Need advice on what which course to take?
Contact us with your goals and background and we will provide some suggestions.
Here is the list of courses –
Data Mining
and Prediction
Applied Predictive Analytics,
in partnership with CrowdANALYTIX
Data Mining in R - Learning
with Case Studies
Data Mining: Unsupervised
Techniques
Decision Trees and Rule-Based
Segmentation
Political Analytics
Predictive Analytics 1 -
Machine Learning Tools
Predictive Analytics 2-
Neural Nets and Regression
Data
Analytics
Cluster Analysis
Discrete Choice Modeling and
Conjoint Analysis
Forecasting Analytics
Interactive Data
Visualization
Introduction to Social
Network Analysis
Logistic Regression
Statistical Analysis of
Microarray Data with R
Using R
Data Mining in R - Learning
with Case Studies
Graphics in R
Mapping in R
Modeling in R
R for Statistical Analysis
R Programming - Advanced
R Programming - Intermediate
R Programming - Introduction
1
R Programming - Introduction
2
Visualization in R with
ggplot2
Text
Analytics
Natural Language Processing
Sentiment Analysis
Text Mining
Operations
Research and Risk
Advanced Optimization
Financial Risk Modeling
Introduction to Optimization
Introduction to Quantitative
Risk Analysis
Risk Simulation and Queuing
IT/Programming
Advanced Analytics and
Machine Learning with Hadoop
Introduction to Analytics
using Hadoop
Introduction to Python for
Analytics
Social Data Mining With
Python
SQL and R - Introduction to
Database Queries
Biostatistics
Advanced Survival Analysis
Biostatistics 1
Biostatistics 2
Epidemiologic Statistics
Meta Analysis
Meta Analysis 2
Sample Size and Power
Determination
Statistical Analysis of
Microarray Data with R
Survival Analysis
Clinical
Trials
Adaptive Designs for Clinical
Trials
Biostatistics in R: Clinical
Trial Applications
Clinical Trials -
Pharmacokinetics and Bioequivalence
Introduction to Statistical
Issues in Clinical Trials
Safety Monitoring Committees
in Clinical Trials
Sample Size and
Power-Analysis for Cluster-Randomized and Multi-Site Studies
Social
Science
Advanced Structural Equation
Modeling
Analysis of Survey Data from
Complex Sample Designs
Introduction to Assessment
and Measurement
Introduction to Structural
Equation Modeling
Many-Facet Rasch Measurement
Modeling Longitudinal and
Panel Data: GEE
Practical Rasch Measurement -
Core Topics
Practical Rasch Measurement -
Further Topics
Rasch Applications, Part 1:
How to Construct a Rasch Scale
Rasch Applications, Part 2:
Clinical Assessment, Survey Research, and Educational Measurement
Survey Analysis
Survey Analysis in R
Survey Design and Sampling
Procedures
Spatial
Analytics
Mapping in R
Spatial Analysis Techniques
in R
Spatial Statistics with
Geographic Information Systems
Statistical
Modeling
Advanced Logistic Regression
Advanced Structural Equation
Modeling
Categorical Data - Applied
Modeling
Generalized Linear Models
Introduction to Smoothing and
P-spline Techniques using R
Introduction to Statistical
Modeling
Introduction to Structural
Equation Modeling
Logistic Regression
Mixed and Hierarchical Linear
Models
Modeling Count Data
Modeling in R
Modeling Longitudinal and
Panel Data: GEE
Multivariate Statistics
Regression Analysis
Survey
Statistics
Analysis of Survey Data from
Complex Sample Designs
Survey Analysis
Survey Analysis in R
Survey Design and Sampling
Procedures
Bayesian
Bayesian Regression Modeling
via MCMC Techniques
Bayesian Statistics in R
Introduction to Bayesian
Computing and Techniques
Introduction to Bayesian
Hierarchical and Multi-level Models
Introduction to Bayesian
Statistics
Engineering
Advanced Survival Analysis
Introduction to Design of
Experiments
Prediction & Tolerance
Intervals; Measurement and Reliability
Probability Distributions
Statistical Process Control
Survival Analysis
Environmental
Ecological and Environmental
Sampling
Spatial Analysis Techniques
in R
Spatial Statistics with
Geographic Information Systems
Introductory
Calculus Review
Introduction to Statistics 1
AP: Inference for a Single Variable
Introduction to Statistics 2
AP: Working with Bivariate Data
Statistics 1 – Probability and Study Design
Statistics 2 – Inference and
Association
Statistics 3 – ANOVA and
Regression
Methods
Analysis and Sensitivity
Analysis for Missing Data
Bootstrap Methods
Categorical Data Analysis
Cluster Analysis
Introduction to Resampling
Methods
Maximum Likelihood Estimation
Missing Data
Principal Components and
Factor Analysis
Review/Prep
Calculus Review
Designing Valid Statistical
Studies
Introduction to Resampling
Methods
Introduction to Statistical
Modeling
Matrix Algebra Review
Survey of Statistics for
Beginners
We, the Center for eLearning and Training
(C-eLT), Pune, partner with Statistics.com and offer these courses to Indian
participants at special prices payable in INR.
Call: 020 6680 0300 / 322
Websites:
No comments:
Post a Comment