| Career Focused | Online | 1:1 Mentorship | 6 Weeks/3 Months |
There has been a 6.5X increase in data science jobs since 2012.
Average Salary of
a Data Scientist.
Of data science graduates have found jobs since 2011.
RMDS Project Impactor Upskill Program
Your one-stop shop for:
Securing a dream job in data science
Standing out from the crowd with strong employability
Navigating a successful mid-career change
RMDS Lab is a pioneer in developing data science and AI ecosystems, and in offering extensive assistance for data science. We exist to empower students, new graduates and professionals to improve their competency and employability in the data science field through our Project Impactor Upskill Program, which includes:
Online course training
Project Impactor internship and project participation
Data science online portfolio building
RMDS ecosystem resources
Certification and expert recommendation
Who Is This Program For?
College students who want to apply for the master’s degrees in data science related field
New graduates who want to pursue career paths in data science related fields
Professionals who want to advance their careers or navigate a mid career change
High school students who are interested in data science and want to apply for college
What You Can Get From the Program?
Exposure to real-world business problems
Hands-on practice on data science projects
Small group mentoring sessions
Free access to online course learning
Boost your Impact Score to increase the visibility to recruiters
One-on-one career coaching
Data Science professional certification
Online data science portfolio building
Recommendation from industry experts
Complimentary membership to RMDS ecosystem
Every enrolled student will receive a 3-month Premium Membership to the RMDS ecosystem. As a Premium Member, you’ll have a leg up in the field of data science with the exclusive benefits of the free access to our online courses, IM Data annual conference and workflow collections, plus special discounts on deep dive training and much more.
Develop Portfolio Worthy Projects
The best way to learn data science is by working on projects. With RMDS Project Impactor Upskill Program, you’ll complete capstone projects focused on real data science scenarios that you can show to future employers. Project-based mentorship will be provided for technical guidance to help students complete the projects. Each project is 6 weeks. Most students devote 5-10 hours a week to complete a project.
A. Covid-19 Research and Risk Map Project
B. Applying Machine Learning to Create a Web-based Realtime Forecasting System
Partnering with the City of LA and LA County Department of Public Health, this project seeks to create an innovative solution to determine the risk of exposure to COVID-19 in locations in and around the City of Los Angeles. This hands-on experience will provide ideas and concepts to help deepen our understanding of the issues that may increase or decrease COVID-19 exposure risks, how to calculate these risks, while being respectful of data privacy.
Partnering with NASA JPL, this project will cover a complete workflow of data collection, feature extraction, machine learning model building, validation, prediction, and evaluation of hurricane forecast models. You will get hands-on experience in processing satellite data and organizing data for operational hurricane forecasting, with the understanding of methods for feature extraction and data dimensionality reduction and multiple machine learning techniques.
C. Predict the Impact of News Sentiment on the Stock Market
In collaboration with our partner WorldData.AI, this project seeks to create an innovative solution to analyze the effects of news sentiment and biases on daily stock performance for top companies in the oil and gas industry. News sentiments and biases have a significant impact on stock prices and consumer behavior. Students will be provided with the necessary news data, stock market data, macro data and company financial data.
D. Business Analytics Projects: Customer Behaviour Analysis, Market Segmentation, Social Media Data Analysis
RMDS Lab is dedicated to user research and analysis and data-driven decision-making. In this project, students will use company internal data to gain insights from data-driven business analytics, so as to effectively improve user retention, ROI and company effectiveness. Students will perform user cluster analysis, market segmentation, and social media data analysis based on real user data using SQL, Python, and Excel. Besides, students will complete data visualization and reporting using Tableau.
E. Website Recommendation Engine and Personalization System
F. Impact Score: Measure a data scientist’s effectiveness and practical impact
RMDS Lab, one of the largest data science ecosystems, can automatically recommend products that users may be interested in based on their browsing and purchasing history. Students are required to use Python, natural language processing and other related tools and knowledge to analyze and organize user data, create a personalized recommendation system, recommend similar users and similar products, and analyze the strengths and weaknesses of the recommendation system.
As a unique attribute and feature of the RMDS data science ecosystem, The RMDS User Impact Score is a system that measures a data scientist’s practical, tangible impact on society through projects, workflows, and other field-relevant interactions. Using public records and platform user data, the Impact Score demonstrates an individual’s power or capacity to cause a positive effect in direct or intangible ways. The student will use Python and multiple data models to integrate user-related behavioral activities and optimize the evaluation algorithms and models of the impact score.
Project Expert Consulting
RMDS Lab Founder, Thought Leader and Former Chief Data Scientist at IBM
Professor of Marketing, Chair of Department & Director of MSBA, Loyola Marymount University
Principal Scientist, NASA Jet Propulsion Laboratory
Former Vice President, Head of Analytics at Qdoba Restaurants
Testimonials from Project Participants
University of Southern California Data Science Project Impacter
Built and standardized ETL module for recommendation system focus on collaborative filtering and saved at least 50% data fetching time.
Created a recommendation system offline evaluation feature, including parameter tuning and modeling evaluation table for different business scenarios; trained collaborative filtering models using nearest neighbor methods and SVD using the created platform.
Led a team to build COVID-19 risk score calculator for Los Angeles County and merge results to LA County COVID-19 risk map.
Expanded and optimized COVID-19 risk score ETL pipeline with Point of interest (POI) data, footprint data, and LA county health data; reduced 90% time on data collection process with web scraping and hashing functions.