Data Application Lab offers the 16 weeks professional data science bootcamp in Los Angeles, Silicon Valley, and Online.  Each lecture is held for two hours and is hosted on Zoom remotely. The syllabus and flyer for the bootcamp can be read on their official website https://www.dataapplab.com/datascience/ with information of the course material, project information and instructors.
What makes the bootcamp unique, in contrast to other programs, is that it is heavily focused on techniques and their application. All of their instructors have extensive experience in industry and education, making this bootcamp ideal for kick-starting a successful career in data science!
The first 6 weeks contain 6 mini projects to solve real-world problems using data. These projects focus on Probability & Statistics in R, Machine Learning in Python, and Big Data with Hadoop Hive. Other topics discussed in this bootcamp are data visualization, A/B testing, deep learning, data virtualization, and data processing using SparkSQL and DataFrame.
After all of the material is lectured, the last six weeks are utilized to complete two larger projects. These projects bring everything together from the course in order to develop and execute two full data science projects from start to finish. This is great for learning about what it takes to perform data analytics in industry.

Data Application Lab will help students learn the frameworks, theories, and practices that have given rise to business analysis. Our instructors will go through essential business knowledge including Marketing strategies, Segmentation and Targeting, Business Development and Sales, Customer Experience and Pricing, Fraud Detection,  A/B Testing, Key Metrics, Funnel Analysis and others.
The courses combine theories and practices that allow students to figure out how tools can support Business Analyst finish comprehensive tasks. Instructors will introduce the most popular analysis tools such as Excel, MySQL，R and Tableau depend on course design and real situations. All of our course schedules help students get the idea, sharpen computer skills and strong critical thinking. The most important thing is that students will have the confidence to communicate with experienced workers using business and technical language and build the ability to solve problems in real business. So, are you ready to become a Business Analyst?
What will you earn and master from the program through our project cases?
As one of the core business of Internet industry, business analytical skills set is highly desirable in e-commerce companies like Amazon, Groupon, Alibaba, Revolve, and others.
How to collect and process a large number of customer data, what is the key metrics for analysis?
What is funnel analysis and how to improve the conversion rate? How to improve customer acquisition, retention, loyalty, and satisfaction?
How to collect user behavior data through A/B testing to drive a company’s decision making in product iteration and development?
How to compare the effect of marketing multichannel marketing campaign and ROI calculation?
2.  For most companies like Facebook, Linked, Amazon, Google, and others, solid SQL skills are essential in order to pass the first round of business analyst interview as well as tackling data challenge.
What is RDBMS (relational database management system) and data schema?
How to handle data cleaning, data quality control, and exploratory data analysis?
How to improve the efficiency of your SQL query?
3.  For students with a finance background or would like to enter the finance industry, a business analyst could play a significant role in financial areas include fraud detection, loan granting, credit card transactions, customer acquisition.
How to identify high risk users and fraudulent activities based on users economic situation, geographical distribution, user habits, amount of consumption, social media data and other information?
How to utilize the data to establish and optimize the classification/clustering model?
4.  Sales prediction
how to analyze the sales data for each quarter, different categories of goos?
how to calculate sales growth or decline proportions?
how to predict the next quarters’ sales performance?
how to improve and optimize the customer segmentation?
5. Sentiment analysis on Twitter
how to analysis customer feedback and preference based on sentiment analysis using twitter’ API?
6. Data visualization
How to build eye-catching and easy-to-communicate dashboard to present your findings and daily report?