<第1階段> Python編程 & 機器學習模型
您將學習Python語法、基本的線性數據結構和搜索算法、以及工業界主流的傳統機器學習模型，夯實數據科學基礎。
上課頻率: 1個月，每周5節課，每節課2-3小時
第 1 周
Introduction of Data Science
ML Background/Target Quiz
Linear Regression
Logistic Regression
Regularization
第 2 周
Nonlinear Models I - Decision Tree
Model Evaluation - Overfitting, Cross Validation
[Coding] Python Basics 1 variable and syntax
[Coding] Python Basics 2 function and class
[Coding] Python Basics 3 base data structure
第 3 周
Nonlinear Models II - Random Forest, SVM, Gradient Boosting
Feature Selection
Machine Learning Project 1 - User Churn Prediction
[Coding] Python Binary Search
[Coding] Python Array and Sorting
[Coding] Python Practice
第 4 周
Unsupervised Learning I - Principal component analysis
Unsupervised Learning II - Kmeans, Latent Dirichlet Allocation
Machine Learning Project 2 - Natural Language Processing and Topic Modeling
[Coding] Python LinkedList and Recursion I
[Coding] Python LinkedList and Recursion I cont
<第2階段> Python編程 & 統計鞏固
您將進一步學習Python、數據結構和算法知識，鍛鍊Coding能力，並學習數理統計、概率等相關的重要知識點。
上課頻率: 3周, 每周5節課，每節課2-3小時
第 5 周
Hypothesis Testing I
Hypothesis Testing II
[Coding] Exam 1
[Coding] Python Queue and Stack
[Coding] Python Binary Tree
[Coding] Recursion II - recursion on tree
第 6 周
SQL I
SQL II
[Coding] Python Practice
[Coding] Python Practice
[Coding] Python Binary Search Tree
第 7 周
A/B Testing
Conditional Probability & Bayes Rule
[Coding] Python Heap
[Coding] Python Hashtable
[Coding] Python Practice
<第3階段> Data Lab & Python進階
本階段，您將完成4+ Data Lab，通過案例驅動的方式，鞏固提升並綜合運用Python編程、傳統機器學習模型與數理統計知識。
上課頻率: 2周, 每周5節課，每節課2-3小時
第 8 周
Data Analysis Lab - E-commerce system design
Data Analysis Lab - Lending Club data project
[Coding] String I
Resume preparation & job seeking strategy
[Coding] Exam 2
第 9 周
Data Analysis Lab - Fraud Detection
Data Analysis Lab - Time series
Analyst track and data scientist track overview and advisement
[Coding] Recursion III[Coding] Probability, Sampling, Randomization
<第4階段> 商業分析Track
4+案例分析與項目實戰，加強您的分析能力和統計知識，夯實SQL和Python基礎，提升溝通等軟實力，幫助您順利通過商業分析崗位面試。
上課頻率: 1個月, 每周4節課，每節課2-3小時
第 10 周
BA track introduction & Intro to Tableau
Data visualization
Business Analysis Project 1: NYC Taxi & Stock Market
[Coding-for-BA] Queue, Stack
第 11 周
Advanced topic in A/B testing
SQL Lab
Business Analysis Project 2: Netflix content personalization system
[Coding-for-BA] HashTable
第 12 周
Data manipulation in Python
BA Communication
Business Analysis Project 3: Bike Sharing
[Coding-for-BA] String practice
第 13 周
Business Sense
Interview & resume preparation
Business Analysis Project 4: E-commerce Customer Engagement Analysis
[Coding-for-BA] String practice
第 14 周
Interview deepdive I - avoid common mistakes
Interview deepdive II - further improvement
BA Mock Interview I
BA Mock Interview II
BA Mock Interview III
<第4階段> 數據科學Track
4+個機器學習項目實戰，深入講解分布式系統Spark和深度學習TensorFlow等前沿知識，幫助您拿到數據科學崗位offer。
上課頻率: 1個月, 每周4節課, 每節課2-3小時
第 10 周
ML Advanced Topics I - Model Implementation
ML Advanced Topics II - Gradient Boosting Machine
Apache Spark I - Introduction of Apache Spark and ML Library
[Coding] Advanced Tree (segment tree, trie tree)
第 11 周
Apache Spark II - Distributed System Design
Apache Spark III - Data Pipeline with Spark
Data Science Project 1: San Francisco Crime Analysis in Apache Spark
Apache Spark IV - Recommendation System (Collaborative Filtering)
[Coding] Graph Search Algorithm
第 12 周
Apache Spark V - Recommendation System (Model-based Approaches)
Data Science Project 2: Movie Recommendation Engine Development in Apache Spark
Apache Spark VI - Recommendation System (Spark ML Implementation)
Data Science Project 3: Twitter streaming data ETL, Youtube user comments semantic analysis
Deep Learning I - Introduction of Deep Learning
[Coding] Graph Search Algorithm cont
第 13 周
Deep Learning II - Practical Applications with TensorFlow
Deep Learning III - CNN and Image Recognition Project
Deep Learning IV - RNN and Sentiment Analysis Project
Data Science Project 4: Market index prediction based in Deep Learning (TensorFlow)
Python practice II: mock interviews
第 14 周
Data Science Case Study
Machine Learning Mock interview Case study
Data Engineer Mock Interview