Data Scientist

Summer immersion Program offer the same coverage with Our 16-week program, but more intensive schedule, which contains basic data science knowledge teaching, in-progressing Kaggle Competition and several advanced practical projects. Students will master the problem-solving skills through the process of identifying market needs, preparing data, feature engineer, model selection, model optimization, and final result presentation. We will provide our students with the most cutting-edge technology and tools in data science industry, to help them turn into a professional data scientist from scratch, step by step.

Big Data SDE Full Stack

In our 16-week real internship projects, trainees will apply what they have learned from lectures in the first 8-week into practice. You will go through the End-to-End project, from identifying market and technical needs, developing the solution, to testing the initial product and deploying the final product.

Data Analyst in SQL

Our SQL course focuses on programming with T-SQL. It's designed to help students master the core knowledge of SQL.

Growth Hacking

This training program is growth hacking boot camp and it allows you to kill two birds with one stone in a way that other programs do not.

Algorithm

Part I focuses on elementary data structures, sorting, and searching. Topics include array list, linked list, stack/queue, hash table, binary search trees, and heap. Part II focuses on graph and three categories of algorithm: Divide and Conquer, Dynamic Programming and Greedy.

Business Analytics

10-weeks training to transform you into a business analyst role with skill set on industry domain knowledge, basic statistics knowledge, programming skills, reporting skills and Critical thinking thought.

Natural Language Processing

Topics related with Syntactic Processing, Semantic Analysis, Information Retrieval, Chart Parsing and etc, will be covered. Practical projects with real-world data will also be offered to students, along with step-by-step instruction on how to improve your results.

Python

The class aims to introduce python to students who are interested in Python. Students require to have some experiences in programming with any language, college level math & dedicated study time.

Programming in Java

Pre-requirement class for Big Data Engineer Bootcamp This course introduces fundamental structured and object-oriented programming concepts and techniques, using Java, and is intended for all who plan to use computer programming in their studies and careers. Topics covered include basics of java, like variables, arithmetic operators, control structures, arrays, functions, recursion, dynamic memory allocation, files, […]

Quantitative Finance Interview Training

We will cover 100 interview questions in quantitative finance including desk quant, quantitative trading, quant researcher, quant strategist, and risk management position in both sell side and buy side.

FinTech Big Data

Add to Cart   Financial technology, also known as “FinTech”, is the use of new technology and innovation in the marketplace of traditional financial institutions and intermediaries. The FinTech Big Data program teaches students the cutting-edge technology and the best practices in the industry with case studies and real-world projects.   For Chinese introduction, Please see […]

Data Science Fullstack

Add to Cart   Full-stack Data Science Engineering is the integration of data science and data engineering.   A full-stack data scientist has a broad understanding of data science product life-cycle shown as blow:   For Chinese introduction, Please see here:   Career Goal: Software architect:  a software expert who makes high-level design choices and […]

Supply Chain Management

Add to Cart   Supply Chain Management(SCM) boot camp is an intensive 4 weeks training program to equip students with industry-specific skills for supply chain management within the big data context.   For Chinese introduction, Please see here:   Topics: – Predictive modeling technology, simulations – Network design, routing, inventory optimization – SCM applications with […]

Data Scientist Interview

项目介绍   Data Scientist面试冲刺班,针对特定群体需求,通过4周共计40课时的训练,对DS岗位所要求的技能和知识体系进行系统性梳理,同时配合进行大量实战面试题型的训练,迅速提升学员在技术面试环节的实操能力和通过率。项目还包含了行业导师简历修改、模拟面试的支持,为求职者在DS及相关岗位面试的各个环节当中发挥出自己的最佳水平提供了全面支持。   面向人群   正在Data Science相关专业学习,将来希望从事Data Scientist相关工作的人群; 有一定Data Science基础,希望转行进入Data Scientist相关行业的人群; 手握Data Scientist,Data Engineer, Business Analyst等相关岗位面试offer,急需提升面试技巧,解决技术面试难题的人群; 对Data Scientist岗位要求缺乏了解,对面试题型不熟悉,缺乏面试经验的求职者。   项目特色   项目周期短,迅速完成能力提升,助力面试成功; 精准聚焦面试要求,反复练习,以“新东方式”冲刺模式,解决面试难题; 强大数据库支持,各大公司全真面试题型练习和解析; 现任高科技公司专家亲自授课,第一手行业资讯和面试经验。     强大师资   来自Microsoft、LinkedIn、Facebook、Amazon等行业领军企业的一线专家亲自授课,精讲例题,分享最新大公司用人需求、录用标准、技术方向等最新资讯,同时从面试官的角度为学员分析面试技巧、考察重点以及面试准备过程中的误区等实用资讯。   本期课程   时间: 3月9日-4月4日(4 周,共计40课时) 课程安排: 周二周四(5-7PM) 或 视课程具体时间安排、周六周日(1-4PM) 课程内容: 1) 周六、周日:理论学习(6 hours) 2) 周二、周四:面试题型精讲和练习(4 hours) 3) 涵盖Probability/Statistic/ML/Data Challenge/SQL/Case Interview/Python Programming/Algorithm Add […]

Data Scientist Interview

点击提交课程申请   项目介绍   Data Scientist面试冲刺班,针对特定群体需求,通过4周共计40课时的训练,对DS岗位所要求的技能和知识体系进行系统性梳理,同时配合进行大量实战面试题型的训练,迅速提升学员在技术面试环节的实操能力和通过率。项目还包含了行业导师简历修改、模拟面试的支持,为求职者在DS及相关岗位面试的各个环节当中发挥出自己的最佳水平提供了全面支持。   面向人群   正在Data Science相关专业学习,将来希望从事Data Scientist相关工作的人群; 有一定Data Science基础,希望转行进入Data Scientist相关行业的人群; 手握Data Scientist,Data Engineer, Business Analyst等相关岗位面试offer,急需提升面试技巧,解决技术面试难题的人群; 对Data Scientist岗位要求缺乏了解,对面试题型不熟悉,缺乏面试经验的求职者。   项目特色   项目周期短,迅速完成能力提升,助力面试成功; 精准聚焦面试要求,反复练习,以“新东方式”冲刺模式,解决面试难题; 强大数据库支持,各大公司全真面试题型练习和解析; 现任高科技公司专家亲自授课,第一手行业资讯和面试经验。     强大师资   来自Microsoft、LinkedIn、Facebook、Amazon等行业领军企业的一线专家亲自授课,精讲例题,分享最新大公司用人需求、录用标准、技术方向等最新资讯,同时从面试官的角度为学员分析面试技巧、考察重点以及面试准备过程中的误区等实用资讯。   本期课程   时间: 3月9日-4月4日(4 周,共计40课时) 课程安排: 周二周四(5-7PM) 或 视课程具体时间安排、周六周日(1-4PM) 课程内容: 1) 周六、周日:理论学习(6 hours) 2) 周二、周四:面试题型精讲和练习(4 hours) 3) 涵盖Probability/Statistic/ML/Data Challenge/SQL/Case Interview/Python […]

Artificial Intelligence

This course is also offered in other languages.  For language in 中文, please refer to this webpage(dataapplab.com/ai)  for details. Week 1 & 2 – Machine Learning Topic 1 Regression Topic  2 Classification Topic  3 Dimension Reduction Topic  4 Clustering Week 3 & 4 – Deep Learning Basic & Computer Vision Topic  1 Computer Vision, Neural […]