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Up Skills: Data Science In-Depth

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Up Skills: Data Science In-Depth

We will start you off with how to gather and organize data, where you will master the use of Jupyter notebook, pandas, matplotlib, data gathering tools via scraping and public API access, and outlier detection. After that, you can choose from the following modules, each featuring hands-on instructions using real-world cases.

Fundamental Series

Data Exploration and regression
(1-day module)
Exploratory data analysis (EDA) techniques, clustering, dimensionality reduction, regression, trend analysis, time-series analysis.

Predictive analytics
(3-day module)
Machine learning methodology, bias vs. variance, model evaluation, tree-based algorithm (decision tree, random forest), linear classifier (perceptron, logistic regression, SVM, kernel SVM), ensemble learning (bagging, boosting)

Applied Series

Image processing and OCR
(2-day module)
OpenCV, optical character recognition

Deep learning for image classification
(2-day module)
Neural networks, stochastic gradient descent (SGD), building a CNN for image classification, deep learning + image classification projects.

Visualization
(2-day module)
Using Dash by Plotly, tables, charts, effective visualizations, visualization projects.

Program Leaders

  • Dr. Sunsern Cheamanunkul
  • Dr. Piti Ongmongkolkul
  • Dr. Weerapong Phadungsukanan
  • Asst. Prof. Dr. Kanat Tangwongsan

Key Learning Points:
After completing the course, the participants will be able to

  • Implement a data science/analytics workflow, specializing in the chosen modules.
  • Use an appropriate set of techniques for a scenario at hand, explain the reasoning behind their choice, and make scientifically-sound interpretations from the outcomes.

Who should attend the course?

  • Beginning data scientists who wish to have a deeper understanding of the techniques
  • Individuals with stats, computing, or math backgrounds who wish to have a firm grasp of data science and work in the arena with confidence.

Key benefits of attending the course:
Knowing how to push a few buttons to apply the most common techniques can only get you so far. This action-packed short course goes much further. Through real-world case studies, we’re going to the deep end of data analytics and modeling. Depending on which modules you choose, you’ll learn how each standard technique works under the hood, enough to know what techniques to try in what scenarios, why to use them, and how to interpret the outcomes.

MUIC Executive Education

Room 1110, Ground Floor, Building 1
Phone: +66 (0) 2700 5000 #1022, 1712
Mobile phone. 084 656 6810
Fax: +66 (0) 441 0233
Email: ictraining@mahidol.ac.th
Mon – Fri 8:00 am – 5:00 pm