Technical workshops are in high demand at The Wharton School. General Assembly told me they were sending their best instructor to teach the students at Wharton, and after attending the workshop myself I couldn’t agree more. Henry Xie did an amazing job teaching a bunch of true Python novices the ins and outs of the program in a very intuitive way. Henry mixed in hands-on exercises throughout the workshop, which provided the students with an opportunity to apply their learning right away. The overall structure of Henry’s Python workshop was very well designed, and our students benefitted greatly from his expertise.
Several students followed up with me after the workshop, and told me how much they appreciated Henry’s thoughtful approach to teaching Python to a group of beginners. We here at the Wharton Customer Analytics Initiative were so pleased and impressed with Henry’s workshop that we decided to bring him back to lead more advanced workshops in Python and SQL. I value the relationship we have with Henry Xie and General Assembly, and I look forward our continued collaboration on future workshops.
The Wharton School
I had the pleasure of working with Henry Xie as he was contracted to deliver Python Training services for 18 programmers at my organization, part of the US Navy. Every student came away from the 4 day course with increased confidence in their Python abilities and had all learned something, including those with past training.
Henry’s training approaches were considered well-paced and he was able to effectively communicate with the class in such a way that all felt personally engaged and cared for.
All the students were dismayed when he was not available for a follow-up Python Training as they had nothing but praise for Henry, his teaching methods, his level of organization and ability to adapt to the class.
Students commented: “Best instructor that I’ve ever experienced,” “Best training I’ve had in years,” “Exceeded my expectations.”
Training and Readiness Department Head at US Navy
Henry is an outstanding instructor. I took a 1 week course in the Python programming Language (introductory) with Henry as the instructor. I was able to rapidly understand this otherwise complex material as a result of Henry's clear, concise, and personable teaching style. He was highly responsive to student needs, contending with a diverse audience of varying levels of computer expertise. In addition, Henry was quick to help me with a programming problem that I was attacking at work. His insight (including code snippets that I plan to use in the near future) was most valuable. I recommend him for any future training needs.
Meteorologist at FNMOC, US Navy
Suneel and Henry were incredibly helpful. They customized the Python and Pandas workshops to Handy's specific data set and business problem, which brought the material to life. Conducting the class in person made for a better team-bonding experience that was more collaborative and conducive to questions.
We brought in Suneel from SimpleFractal for a Python boot camp for our BI and Finance teams and we found him to be a great instructor. The agenda and pace felt well planned, and we all felt we came away with a solid grasp of the fundamentals. I would definitely recommend SimpleFractal, especially for those looking for a more tailored experience.
Intro to Python
Build a strong foundation in Python and prepare for more advanced workshops. No prior programming experience is required.
Learn more advanced Python techniques with plenty of hands-on exercises. Exercises include performing data analysis on a real data set read in via csv.
Web Programming with Python
Learn to use Python for web development through the popular Django framework. Concepts covered include MVC, routing, templating, database management and much more.
Pandas for Data Analysis
Learn to use Pandas, a powerful Python library for data science. Students should have taken Intermediate Python or equivalent.
Data Science with Python
Learn to read in, munge, and prepare data with Pandas and get hands-on experience building predictive models with Scikit-learn, for example predicting Boston house prices and building breast cancer detector.
Clustering and Dimensionality Reduction
Learn to apply unsupervised machine learning by performing cluster analysis, including KMeans and hierarchical clustering. Learn why, how and when to use dimensionality reduction, such as Principal Component Analysis (PCA).
Neural Networks and Deep Learning
Get an introduction to the perceptron model of neural networks and begin actually training neural networks to solve classification problems, build convolutional neural networks for image detection, and finally get hands-on exposure to deep learning using TensorFlow or Lasagne.
Cluster Computing with Spark and Hadoop
Learn how map reduce works, what Hadoop is, how to use it, how Spark is different, and get practical experience writing code for Spark, using the built-in machine learning modules and parallelizing massive computations.
Natural Language Processing with Python
Learn the core techniques of natural language processing, from tokenization to TFIDF, using nltk and scikitlearn. As a concrete application, you will build a document categorization engine.
Recommender Systems with Python
Learn how to apply machine learning techniques to build a recommendation engine. You will be able to explain online versus offline training, and in particular apply online training to build a live movie recommendation engine that updates according to user feedback. You will experiment with different predictive models, such as Random Forest, Neural Networks, and Logistic Regression to determine which technique leads to the most accurate predictions.
Learn how to use the Python Imaging Library and OpenGL to automate image processing and prepare image data for the predictive modeling step. Them, you will apply various classification algorithms, from Logistic Regression to Convolutional Neural Networks to solve problem such as human face detection.
Advanced Regression Techniques
Learn how to use regularization and other advanced regression techniques to produce better models. You will use statsmodels as well as Scikit-learn to put your knowledge into practice.
Working with Big Data
Learn what big data is, what Hadoop is, and how to use the various parts of the big data ecosystem to your advantage. We will go through case studies of how big data provided business value to certain companies and outline practical steps to get started with using Big Data to make data-driven decisions.
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