Do you know anyone who needs a well-trained Data Scientist?

This article introduces Singapore's first cohort of METIS Data Scientist Bootcamp attendees.

From 8th of July 2019 to 28th of September 2019, 11 of us in this 12-week full-time, Monday to Friday, 9 am to 6 pm training (Plus numerous weekends and late nights) went through the most thorough training in data science. Each of us came with different working experiences in different industries and together we completed the course with one group project (3 or 4 in a group) and four individual projects in different areas and we literally went through the learning of data science from start to end, head to toe, with lots of theories and hands-on sessions for different topics. Here's a summary of what we had gone through:

Online Pre-Work

25 hours minimum of academic pre-work and variable hours to setup.

Bootcamp Summary

Week 1: Introduction to the Data Science Toolkit

Exploratory Data Analysis, Bash, Git & GitHub, Python, pandas, matplotlib, Seaborn

Week 2: Linear Regression and Machine Learning Intro

Web scraping via BeautifulSoup and Selenium, regression with statsmodels and scikit-learn, feature selection overfitting and train/test splits, probability theory.

Week 3: Linear Regression and Machine Learning Continued

Regularisation, hypothesis testing , intro to Bayes Theorem

Week 4: Databases and Introduction to Machine Learning Concepts

Classification and regression algorithms (Knn, logistic regression, SVM, decision trees, and random forest), SQL concepts, cloud servers

Week 5: More supervised learning algorithms & web tools

Naive Bayes, stochastic gradient descent and intro to Deep Learning, Full stack in a nutshell: Python Flask, Javascript and D3.js

Week 6: Statistical Fundamentals

MLE, GLM, Distributions, Databases (RESTful APIs, NoSQL databases, MongoDB, pymongo) Natural Language Processing techniques

Week 7: Unsupervised Machine Learning

Various clustering algorithms, including K-means and DBSCAN, dimension reduction techniques (PCA, SVD, LDA, NMF)

Week 8: More Deep Learning & Unsupervised Learning

Deep Learning via Keras, Recommender Systems

Week 9: Big Data

Hadoop, Hive & Spark, Final project initiated

Week 10-12: Final Project

For the recruiters of data scientists, please do not miss this opportunity to get yourself a fully trained, well-equipped data scientist. For those who know any company that is looking for a data scientist, please help to refer.