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Dr. Andre Zitzke, Prof. Temesgen

Trainers

  • Online
  • 22-02-2021 to 27-02-2021

1. SAS SOFTWARE

SAS is the only vendor, consistently a leader for seven years in a row, in the 2020 Gartner Magic Quadrant for Data Science & Machine Learning Platforms. According to Gartner, our position is due to the key strengths of trust in the SAS brand, support for full ModelOps, and ease of use..

Apply Now Price:250$ More Info about SAS
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Dr. Vedaste Ntalindwa, Muhamed Semakula+ARISE Network

Trainers

  • Online
  • 08-03-2021 to 12-03-2021

2. Quantitative Monitoring and Evaluation Methods

Topics to be covered

  1. Introduction to quantitative methods in M&E
  2. M&E design: Frameworks for and levels of evaluation and indicators
  3. using statistics to make inference about program Variability, Inference, Probability
  4. Complex survey samples: Design and Analysis
  5. Lot Quality Assurance (LQAS) Methods: Introduction, Design and Implementation, Integrating with Survey Sampling
  6. Levels of Evaluation
  7. Statistical analysis of Clustered and aggregate data
  8. Common sources of error (Missing at Random (MAR), Missing Not at Random (MNAR), Pool
  9. (Group) Testing)
  10. Bias Mitigation (Multiple Imputation, Estimation & Rep Steps, pooling Step and Standard Error, Randomized Response, Annealing, Lying)
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Dr. Ignace Kabano,Dr. François Niragire+ARISE NETWORK

Trainers

  • Online
  • 15-02-2021 to 19-02-2021

3. Methods of Data Management with Software Applications

  1. State the principles of producing high-quality data
  2. Develop questionnaires and identify problems with existing questionnaires from a data quality perspective
  3. Design electronic data collection tools that produce high-quality data
  4. Develop data collection procedures for producing high quality data
  5. Monitor data and adjust data collection procedures
  6. Clean data
  7. Produce meaningful summary statistics, graphs, and data monitoring reports
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Dr. Joseph Nkurunziza,Dr. Innocent Ngaruye

Trainers

  • Online
  • 15-03-2021 to 19-03-2021

4. Complex Sample Survey Analysis

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Dr. Richard Kabanda

Trainers

  • Online
  • 17-05-2021 to 21-05-2021

5. Panel Data Analysis in Finance

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Harvard Data Science Initiative(Weiwei Pan,Javier Zazo

Trainers

  • Online
  • 21-06-2021 to 25-06-2021

6. Machine Learning and Computational Statistics

  1. Statistical learning theory framework, stochastic gradient descent, Matrix/vector differentiation
  2. Excess risk decomposition, LI/L2 regularization, Lasso algorithms, sub-gradient descent
  3. Loss functions, convex optimization, Support Vector Machine ernels, kernel ridge regression, kernelized Support Vector Machine; Trees, bias and variance decomposition
  4. Ensemble algorithm methods: bootstrap, bagging. random forest. AdaBoost
  5. Gradient boosting, neural networks Spring Break
  6. Natural exponential families and generalized linear models
  7. Bayesian networks, class-conditional models, naive Bayes
  8. Clustering, Gaussian mixture models, EM algorithm
  9. Bayesian methods, hierarchical models, Gibbs sampling, Singular Value Decomposition,PCA, Linear Discriminant Analysis
Apply Now $400
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Sara Sauer,Muhammed Semakula

Trainers

  • Online
  • 21-06-2021 to 25-06-2021

7. Statistical Simulation

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