来Offer-人工智能与数据科学强化课程2021|价值56000

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机器学习理论+Python编程基础
您将学习Python语法、基本的线性数据结构和搜索算法、以及工业界主流的传统机器学习模型,夯实数据科学基础。

上课频率: 1个月,每周5节课,每节课2-3小时

第1周
Introduction of Data Science

Fundamentals of Probability

[Coding] Python Basics 1 variable and syntax

第2周
[Coding] Python Basics 2 function and class

Linear Regression & Logistic Regression I

[Coding] Python Basics 3 base data structure

[Coding] Python Binary Search

Logistic Regression II & Regularization

第3周
[Coding] Python Array Basic Sorting

Model Evaluation

[Coding] Python LinkedList and Recursion I

[Coding] Python LinkedList & Recrusion I cont

Nonlinear Models I

第4周
[Coding] Python Practice

Nonlinear Models II & Feature Selection

[Coding] Python Advanced Sorting and Practice

[Coding] Python Review

PCA & Unsupervised Learning

第2部分
概率与统计知识 & Python编程进阶
您将进一步学习Python、数据结构和算法知识,锻炼Coding能力,并学习数理统计、概率等相关的重要知识点。

上课频率: 3周,每周5节课,每节课2-3小时

第5周
Data Manipulation in Python 1

[Coding] Python Queue and Stack

[Coding] Python Advanced Sorting and Practice

Data Manipulation in Python 2

[Coding] Python Review

[Coding] Python Review

[Coding] Exam 1

第6周
Machine Learning Project 1 – Customer Churn Prediction

[Coding] Python Binary Tree

[Coding] Recursion II – recursion on tree

Machine Learning Project 2 – NLP and Topic Modeling

[Coding] Python Practice

第7周
Introduction to statistics

[Coding] Python Binary Search Tree

[Coding] Python review

Resume and Interview Preparation I

Resume and Interview Preparation II

A/B testing 1

[Coding] Python Heap

A/B testing 2

第8周
A/B testing 3

[Coding] Python Review

A/B testing 4

Inference in regression

第9周
[Coding] String I

SQL I

[Coding] Recursion III DFS

[Coding] Recursion III DFS cont

SQL II

第3部分
OA经典案例分析与简历辅导
本阶段,您将学习经典Online Assessment破题思路,了解如何选择track,并获得深入准备和提升简历。

上课频率: 2 周, 每周5节课,每节课2-3小时

4+案例分析与项目实战,加强您的分析能力和统计知识,夯实SQL和Python基础,提升沟通等软实力,帮助您顺利通过商业分析岗位面试。

上课频率: 1个月,每周4节课,每节课2-3小时

第11周
BA track introduction

BA track mock interview

[Coding-for-BA] Queue, Stack

第12周
eCommerce deep dive 1: System design

eCommerce deep dive 2: Data driven marketing

eCommerce deep dive 3: Data lab

[Coding-for-BA] HashTable

第13周
eCommerce deep dive 4: Data lab

Data visualization In Tableau

Data visualization in Python

[Coding-for-BA] String practice

第14周
Case study deep dive 1

Case study deep dive 2

Case study deep dive 3

Anomaly Detection 1

第15周
Anomaly Detection 2

Anomaly Detection 3

Supply chain data 1

Supply chain data 2

第16周
Review of BA/DA track

商业/数据分析Track
数据科学/工程Track
7+个机器学习项目实战,深入讲解分布式系统Spark和深度学习TensorFlow等前沿知识,帮助您拿到数据科学岗位offer。

上课频率: 1月, 每周4节课, 每节课2-3小时

第11周
Big data and ML I: Data pipeline

Big data and ML I: Course project introduction

[Coding] Advanced Tree (complete tree, segment tree, trie tree)

第12周
Big data and ML II: Spark RDD, SQL, DataFrame

Big data and ML III: Spark ML

Big data and ML IV: Spark ML and CTR

[Coding] Graph Search Algorithm

第13周
Big data and ML V: Recommendation system

Big data and ML VI: Apache Spark and Flink Streaming

ML Advanced Topics I – Model Implementation

[Coding] Graph Search Algorithm Cont

第14周
ML Advanced Topics II – Gradient Boosting Machine

ML Advanced Topics III – Data Science Case Study

ML Advanced Topics IV – XGBoost Practice

[Coding] Python practice: mock interviews

第15周
Deep Learning I – Neural Network Basics

Deep Learning II – Implement Neural Network from Scratch

Spark lab practice and code review

Deep Learning III – Convolutional Neural Network

第16周
Deep Learning IV – Recursive Neural Network

第10周
[Coding] Exam 2

SQL III

Stats review

[Coding] Probability, Sampling, Randomization

Resume and interview preparation

Career guide: BA vs DS

Online Assessment – deep dive 1

Online Assessment – deep dive 2

商业/数据分析Track
数据科学/工程Track

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