Data Science Bootcamp (Part-Time)

Applied Data Science & Big Data

If you are a new graduate or career switcher interested in a data scientist career path, WeCloudData’s Data Science bootcamp is the best option. We offer the most structured data science learning path. Students learn with hands-on projects, build real experience via industry data projects, and receive six months of career mentorship to help them land a data scientist job. Our data science bootcamp is consistently ranked as one of the top coding bootcamps. Inquire today to become a data scientist with WeCloudData.

Intermediate
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Part-time

Online Live

6 months
260 hours
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About the Program

The Applied Data Science & Big Data Diploma Program (Data Science Bootcamp) is a part-time flexible learning program that helps recent graduates and career switchers break into data science. The learning package includes 26 weeks of part-time study, six months of portfolio project building, and six months of 1<>1 mentorship and job support after graduation. WeCloudData is committed to an extensive support period to help our learners achieve their career change/kickstart dreams. If you want to make a smooth transition to becoming a data scientist, and reduce the friction and frustration by following a structured curriculum, while keeping your daytime job, this program will become your best career investment.

POTENTIAL JOB TITLES
Data Scientist
Machine Learning Scientist
Statistical Analyst
Big Data Analyst
Decision Scientist
Machine Learning Engineer
Predictive Modeler
Statistician
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WeCloudData is the perfect place to grow your career

Choose your network & mentor wisely
Interacting with expert instructors, engaging with classmates, working on group projects, meeting with real clients and networking with a community of like-minded professionals. You'll be able to build your network and collaborate with people from all backgrounds, strengthening bonds and making friends in the process!
Solving real-world problems
In our bootcamp, we'll give you an opportunity that many graduates don't have: work on something meaningful and important right away. You will be able to even contribute ideas or solutions that make an impactful change! Teamwork is an essential part of data career. In our bootcamp, we'll have you work with other students and a Project Manager to complete a Real-Client project.
Comprehensive bootcamp with a focus on skills that are in high demand
No other bootcamp offers the flexibility and variety of topics, the number of hours and instructors, and the depth of knowledge in this industry. WeCloudData is a one-stop destination to learn data science - from basic concepts to building data-driven applications. Your learning is personalized and all your questions are answered by our expert instructors.
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Ranked #1 Data Training Program

4.9/5
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A path more than just courses

REAL HANDS-ON PROJECTS

Gain hands-on experience with Real-client Project

The Data & AI Job Market is highly competitive. It is easier to stand out and get noticed with relevant background and experience. Therefore, WeCloudData has gone the extra mile to bring real-life projects into the classroom. Our Part-Time Data Science Bootcamp students will work on real business scenario-based projects. The Full-Time Data Science Bootcamp students will get opportunities to work on real client projects.
Portfolio Project

Build real project experience to differentiate

We also have a capstone project that gives our students the chance to synthesize their learning and build a portfolio piece they can showcase on their resume or LinkedIn profile. This helps them stand out from other applicants when applying for jobs or opportunities.

LEARNING EXPERIENCE

Drive Success with Interactive Learning Experience

Weekly Schedule
Monday
Our teaching assistants will provide 1-1 help on lab challenges. Lab instructors will also give project mentorship. It’s important to take advantage of the live office hour sessions.
Tuesday
Learners join live zoom sessions to learn new topics of the week. The instructor will spend 2 hours on theory, use cases and 1 hour on hands-on demo. Students are encouraged to follow along and ask a lot of questions.
Wednesday
Same as Monday office hour. Sessions can be live or async via slack.
Thursday
Learners join live zoom sessions to learn new topics of the week. The instructor will spend 2 hours on theory, use cases and 1 hour on hands-on demo. Students are encouraged to follow along and ask a lot of questions.
Friday
Same as Monday office hour. Sessions can be live or async via slack.
Saturday
Lab instructors will go through lab exercises. During some sessions students are required to work in groups and complete peer coding challenges. Lab instructors will discuss lab solutions and let students ask specific questions.
* Mon-Fri Regular Hours
* For learners who are also enrolled in the real projects, they work with our project leads and real life projects. Full-time job seekers will spend more time during the week and professionals with full-time jobs will collaborate asynchronously with the project team throughout the week.
Bootcamp Journey
FACULTY TEAM

Learn from the best instructors & TA

We’ve brought together a team of highly skilled and experienced instructors to help you learn effectively. Our instructors have a passion for teaching and a wealth of real-world experiences in their respective fields, so you can be confident that you’re learning from the best.

CURRICULUM

Be ready for the new economy

WeCloudData Bootcamps are designed to be project-based. We not only cover essential theories, but also teach how to apply tools and platforms that are in high demand today. Our program curriculum is also highly adaptive to the latest market trends. 

MODULE 1
Data Science with SQL
This module introduces learners to SQL, one of the essential data analytics skills. Students will learn to write SQL queries to extract, transform, aggregate, pivot, and join data. Students also learn to apply Tableau and SQL for visual storytelling under various contexts.
LEARNING OUTCOMES
  • Apply advanced SQL functions to analyze financial market time series data
  • Analyze the latest trends in Web3 and OpenAI ChatGPT using SQL
  • Design visual storytelling on retail data with Tableau and SQL
  • Data preparation for machine learning with SQL
KEY SKILLS
  • Database (RDBMS)
  • SQL
  • Data Extraction
  • Data Transformation
  • Data Aggregation
  • Analytic Functions
  • SQL Performance Tuning
  • Data Exploration
  • Data Preparation
Tools:
MySQL
Datagrip
Tableau
Database
Twitter
OpenAI
Tools:
Python
Jupyter
NumPy
Pandas
Plotly
OpenAI
Streamlit
MODULE 2
Data Science with Python
This module teaches students some of the most practical data science and analytics skills using Python. Students will start with python programming basics and move towards advanced topics such as DataFrame, visualization, web scraping, database integration, and building interactive apps using Streamlit. The module focuses on building things that are fun and practical for businesses.
LEARNING OUTCOMES
  • Master the fundamental python programming skills
  • Analyze and manipulate structured and unstructured data using Pandas DataFrame
  • Collect data from the web using scraping techniques
  • Work with web and data APIs such as OpenAI ChatGPT and Twitter
  • Database integration via SQLAlchmey and Psycopg2
  • Visualize data and discovery patterns using Pandas, Matplotlib, and Plotly/Seaborn
  • Build interactive visual applications with Streamlit
KEY SKILLS
  • Python
  • Data Structure
  • Functions & Modules
  • Pandas DataFrame
  • Exploratory Data Analysis
  • Web Scraping
  • HTML Basics
  • BeautifulSoup
  • Selenium
  • Data APIs
  • Database Integration
  • Python Packaging
MODULE 3
Applied Machine Learning
The Machine Learning unit introduces students to machine learning, including the concepts, algorithms, and techniques used to train and deploy machine learning models. Students will learn about supervised and unsupervised learning and popular algorithms such as linear regression, decision trees, random forests, and xgboost, and deep neural networks. Students will be learning end-to-end machine learning pipelines, and work on solving various practical ML challenges.
LEARNING OUTCOMES
  • Gain mathematics intuition about machine learning
  • Understand the fundamental concepts of machine learning, including supervised and unsupervised learning
  • Evaluate the performance of a machine learning model and use techniques such as cross-validation to improve it
  • Build machine learning pipelines by following the industry best practices
  • Apply popular machine learning algorithms to solve real-world problems
  • Learn when and how to apply machine learning techniques in different business scenarios
  • Learn how to apply ML solutions to have real-life business impact
  • Understand how to communicate effectively and build trust with business teams via ML storytelling
KEY SKILLS
  • Math (Statistic, Linear Algebra)
  • EDA (Exploratory Data Analysis)
  • Feature Preparation
  • Feature Selection
  • Feature Engineering
  • Regression Analysis
  • Classification
  • Ensemble Trees (GBM, XGBoost, Random Forest)
  • Model Validation
  • Hyperparameter Tuning
  • Clustering
  • Deep Neural Networks
  • Deep Learning
  • NLP
  • Text Classification
  • Sentiment Analysis
Tools:
Python
Pandas
NumPy
SciPy
Sklearn
PyTorch
Streamlit
Tools:
Linux
AWS
EC2
S3
Athena
Redshift
Hadoop
EMR
Databrick
Quicksight
MODULE 4
Big Data
The Big Data unit introduces students to big data, including the concepts, technologies, and techniques used to manage and analyze large data sets. Students will learn about the characteristics of big data, such as volume, velocity, variety, and veracity, as well as the challenges and opportunities it presents. They will also learn about popular big data technologies such as Hadoop, Spark, and AWS and how to build an end-to-end big data analytics projects in the cloud.
LEARNING OUTCOMES
  • Understand the fundamental concepts of big data, including its characteristics and challenges
  • Use popular big data technologies such as Hadoop and Spark to store, process, and analyze big data
  • Understand the basic concepts of distributed computing and how it is used to process big data
  • Understand the basic concepts of data visualization and how it can be used to present big data insights
  • Build an end-to-end real-time data science pipeline using AWS, Kinesis, Spark, Spark ML, Athena/Presto, and Quicksight
KEY SKILLS
  • Big Data
  • Apache Spark
  • AWS EC2
  • AWS S3
  • AWS Redshift
  • Distributed Systems
  • Data Ingestion
  • Distributed Machine Learning
  • Real-time Analytics
  • Federated Queries
  • End-to-end data science pipelines
Module 5
Business Use Cases & Agile Project Management
This module prepares students for the real world. Students will work peer-to-peer on solving multiple data science challenges. The instructors will cover real use cases and bring their real-life project experiences into the classroom. Students also learn how to work in teams and practice agile project management methods in group projects as well as the optional real client projects.
LEARNING OUTCOMES

Some of the use cases covered include

  • Telecom churn prediction
  • Recommender system
  • Supply chain forecasting
  • Retail customer segmentation
  • Social sentiment analysis
  • Bank fraud detection
  • Bank loan approval
  • Ads CTR prediction
  • Insurance claims prediction
KEY SKILLS
  • Business Presentation
  • Use Case Study
  • Agile Project Management
  • Scrum
  • Kanban
  • Diagraming
Tools:
Notion
Lucid
Kanban
Github
PPT
Agile
Tools:
LinkedIn
ChatGPT
Leetcode
Hackerrank
Module 6
Career Preparation
Before entering the 1-1 career mentoring, students will learn about the Data Science job market and build job search skills. Career coaches will teach graduates how to structure resumes, apply for jobs, and ace the interviews. Students work in groups for peer mock interview practice.
LEARNING OUTCOMES

Career services included in the bootcamp include

  • Resume workshops
  • Group interview practice
  • Portfolio project mentoring
  • Coding interview practice and additional resources (Leetcode/hackerrank)
  • Peer programming practice and code reviews

Career services included after graduation (6 months)

  • One-on-one career mentoring sessions with data scientists for 6 months after graduation
  • One-on-one resume critique
  • One-on-one mock interview sessions with data science mentors
  • Job referrals and networking sessions
KEY SKILLS
  • Research
  • Cold Calling
  • Networking
  • Presentation
  • Salary Negotiation
SCHEDULE

Upcoming Start Dates

View Tuition, Financing Options, and Scholarship in the Program Package

Intermediate
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Career Services

Career success takes more than just courses

Taking courses alone don’t guarantee career success. WeCloudData’s career mentoring service, community events, and workshops are top-notch! We put in lots of effort outside of the classes to help learners grow their knowledge, confidence, job skills as well as network.

1-on-1 Mentorship

Available in all bootcamp programs, the career mentorship service helps close job market knowledge gap and provides the support our learners need to land a job.

Networking & Community

WeCloudOpen is a community built for tech leaners, practitioners who want to share thoughts, tips, and best practices with fellow learners and grow together.

Events & Workshops

Catching up with the latest tech industry trends by attending WeCloudOpen Workshops and community events. Learn practical tools and always stay relevant. 

OUR ALUMNI ARE WORKING AT
OPEN RESOURCES

Start Learning With WeCloudOpen

WeCloudOpen is here to help you unlock your full potential in tech, with our free courses and workshop. Learn the fundamentals of coding and data, and become a proficient tech professional in no time!

WeCloudOpen Course

Our comprehensive courses on Python and SQL are the perfect way to start your journey into the world of tech. WeCloudOpen ensures you learn the basics without any hassles

WeCloudOpen Workshop

Our free workshops offer topics like Business Intelligence, Data Science, Data Engineering, DevOps, Machine Learning – allowing you to get a head start in tech career

student success

What our graduates are saying

Pooja Sureja (2022 Alumni)

“Best Bootcamp!!”

I started my journey as a Mechanical Engineer. Making a career transition was hard decision to make. All the teachers and professors have played an important role shaping my professional career. Their care for the students’ well being and their ability to cater to all learning styles was one of the keys to my success. I would definitely recommend this program for all the career switchers. Awesome career service provider. Mentors are well educated and help a lot in resume building, interview preparation.

5/5

Han Liu (2021 Alumni)

  • Overall ⭐⭐⭐⭐⭐
  • Curriculum ⭐⭐⭐⭐⭐
  • Job Support ⭐⭐⭐⭐⭐

 

“Best Bootcamp!!”

The staff at WCD are very professional and supportive. Especially Tianshu and Ernesto, they are very quick response and willing to help me with questions even in late night! Based on my experience, real client projects are the most valuable experience for beginner like me to land job in DS position!

5/5

Shima Sadat (2022 Alumni)

  • Overall ⭐⭐⭐⭐⭐
  • Curriculum ⭐⭐⭐⭐⭐
  • Job Support ⭐⭐⭐⭐⭐

 

“Data Science Program”

A great program! The course content was amazing, well-designed and organized from pre-work courses to milestone assignments and real-life projects. Finally, I could find my favorite job I was looking for. I would recommend this program to everyone at any level.

UPCOMING EVENTS

Join our online webinar

Data & AI Career Guides – Reverse Engineer Job Search
May 23, 2024
8:00 pm -
 10:00 pm
 EST
Data Science and Generative AI as a New Career Frontier
May 28, 2024
8:00 pm -
 10:00 pm
 EST
AMA with Data Career Mentors (bring your questions)
May 30, 2024
8:00 pm -
 10:00 pm
 EST
Use OpenAI to build resume and supercharge your job search
June 4, 2024
8:00 pm -
 10:00 pm
 EST
[Lunch & Learn] AMA: careers in data for new graduates
May 23, 2024
12:30 pm -
 1:30 pm
 EST
[Lunch & Learn] AMA: Data Engineering Q&A
May 24, 2024
12:30 pm -
 1:30 pm
 EST
Data Science Career Workshop (bring your questions)
June 6, 2024
8:00 pm -
 10:00 pm
 EST
[Lunch & Learn] Workshop: Getting Started with AWS
May 27, 2024
12:30 pm -
 1:30 pm
 EST
[Lunch & Learn] Info Session: ML Engineer Bootcamp
May 28, 2024
12:30 pm -
 1:30 pm
 EST
[Lunch & Learn] AMA: Getting Started with DevOps & MLOps
May 31, 2024
12:30 pm -
 1:30 pm
 EST

Let WeCloud Accelerate Your Career in Tech

Start your application

Want more details about this program? Unsure about which path to take? Apply now to reserve a spot or make an appointment with our learning advisor. 

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FAQ

Frequently asked questions about the bootcamp
They follow the same curriculum. The part-time program is 26 weeks long and is suitable for learners who have a full time job and want the flexibility. The full-time program is for learners who have time to study full-time and complete the bootcamp in 12 to 14 weeks. Both options are intense and require dedication.
Data engineers help the organization ingest, collection, and transform large amounts of data. Data engineers deal with raw data and understands data models very well. The output of DE’s work are usually data warehouse or data lakes that store cleansed and transformed data. Data scientists and analysts will consume those data for business intelligence and machine learning/predictive analytics. Data analysts will focus on analyzing data to address ad-hoc business questions. They are good at SQL and database queries and know the business metrics well. Data analysts will also build KPI dashboards that are consumed by business teams and executives for day to day operations. Data scientists perform advanced analytics and machine learning to help the business address predictive questions. It goes beyond answering the what and why questions, and help business make personalized recommendations to improve sales, identifying high-risk transactions to prevent loss, finding good customer segments to generate more revenue, etc.
Yes. It’s possible to watch the recording only without support. It is also possible to watch the recordings and get learning and career mentorship. Please talk to our learning advisors for more details.
Whether you go with a full-time or part-time Bootcamp depends on a few factors. 1. are you able to afford quitting your current job? If not, go with the part-time Bootcamp. 2. How soon do you want the career switch to materialize? If you want it to happen sooner, full-time is a better option. 3. Do you have the grit to have a full-time job while grinding through a busy part-time Bootcamp? If yes, maybe part-time is a better option. Otherwise, full-time Bootcamp gives you the disciplined environment you need to push forward. Quitting your full-time job is generally not recommended during a tough job market or when the market is not bullish. Financial stability is very important and make the decision to quit your full-time job only when you can afford 6-12 months of runway, when your existing busy job doesn’t allow you the luxury to study part-time, or when you need the handholding and concentration to fully immerse yourself in school for a few months.
WeCloudData offers a unique project-based learning approach. Unlike other bootcamps, we give students the opportunity to work on real-life consulting projects as part of the learning journey. The real projects help students gain confidence, show real experience on the resume, get more interviews, have real experience to talk about during the interviews, and adapt to new jobs quickly.
Learners joining the data science bootcamp don’t need to have strong data science experience. The bootcamp is supposed to prepare you for the job market. However, being able to demonstrate basic data handling skills using excel or experience working with tables and spreadsheets are the minimum requirements. Basic data sense and logical thinking is also important. There will be a screening test that the learners need to pass in order to get admitted into the program. If you come from a non-tech, non-STEM, non-CS background, it’s totally fine. However, pre-bootcamp preparation is the key. We highly recommend learners take the Data Fundamentals course before joining the data science bootcamp. It equips them with the right skills to become successful in the bootcamp. If you won’t be available for the data fundamentals course, we recommend you take the free SQL and python courses at your own pace. Completing the data fundamentals course also give learners the opportunities to be eligible for additional scholarship because it shows the commitment to success.
Students who have graduated from the data science bootcamp are a good mix of backgrounds. About half the cohort will be career switchers and professionals who don’t come from data and tech background. 30% of the learners are recent graduates. Some of them are from CS, statistics, and engineering background. 10-20% of learners already have some data analytics skills via self-learning or previous work and they are in the bootcamp to up-skill and learn more about machine learning and big data. About half of the learners have a bachelor’s degree and 40% have a Master’s degree and 10% have PhD background. Almost everyone’s goal is to land a job in data science.
To get the most up to date information about the Data Science job market, we recommend you check out the Job Market Report and blog posts on our website. Typically, data scientists are expected to be paid an average base salary of $120k USD in the U.S. and $100k CAD in Canada. Senior data scientists can be compensated well over $150k USD.
The job market demand for data scientist is very high. It is getting very competitive because there’re more junior data scientists competing for entry level jobs, which are somewhat limited in a tough job market in recent years. However, as an applicant, all you need is an advantage/edge to beat 95% the career switchers and junior DS out there. The best way to achieve this is through project experience building. As long as you have the right skills and relevant industry experience you will have a very big advantage. This is exactly what WeCloudData’s project-based learning can offer. Our 1-1 career mentoring service will also make sure that you have the right interview experience to stand out to employers.
PhD is not required for all DS jobs. Only about 12% of the data scientist jobs specifically mention PhD in the description. 40%-50% of the DS jobs require a minimum of Bachelor’s degree and 30% of the DS jobs require Master’s degree. Of course, having a higher degree will always be an advantage but employers are more interested in experienced candidates. So if you have strong project portfolio and even real project experiences, it weigh much more than education background.
Yes, statistics is important knowledge to have if you want to become a data scientist. But there’s no need to complete a statistics book or course. It’s more important to understand how to use statistics for specific data science scenarios such as AB testing, understanding metrics, understanding statistical learning algorithms. Those don’t require very deep knowledge of statistics and can be picked up quickly. The bootcamp will prepare you for math and statistics. We also highly recommend learners go through the pre-bootcamp.
Most career switchers who don’t have STEM background will have doubts. Based on WeCloudData’s experience, lack of tech background can be quickly overcome by working on practical projects. There’re definitely learning curves to overcome during the bootcamp but that 3-6 months will be worth the effort. Considering that it will have a profound impact on your future career path, it’s worth the pain! Getting into data science or other data professions give you exposure to some of the best job opportunities and you will also have more options to become product managers and project managers in this space. You can also go pretty far down a technical career path. WeCloudData will give you the support and care you need along the way and help you become successful.
Yes. The recent hype in generative AI is real. We’ve seen the power of ChatGPT. Some have fear that jobs like data scientist and analyst will be replaced by ChatGPT. However, one needs to realize that chatGPT is just a language model. It won’t be able to replace a data scientist any time soon. Of course, there’re code interpreters that can even generate code to do analysis, but real analytics tasks require understanding of business context, rules, and data itself. Generative AI is not close when it comes to reasoning and analytics and to create real business value we still need data scientists. The demand for DS and AI talents will also increase due to many business starting to realize the power of data and AI. Being able to write a few lines of code DOES NOT equal data science. Data scientists often need to exert influence on decision making and having emotional intelligence is also extremely important. That is not something ChatGPT can do. But it will help data scientists become more efficient so we should all be adapting to it.
This course is designed to be very hands-on. It’s impossible to become good at data science without actually digging into the data, analyzing it, and developing solutions that will impact business. There will be lots of lab exercises and homework to keep students busy and the projects will help learners gain practical experience. If you prefer a more academic environment, we recommend you consider a Master’s program. If you want to gain practical experience and build portfolio projects, this is the perfect course.
Learners in the part-time program usually spend 15 to 20 hours each week (including the lectures and labs) and learners in the full-time program usually spend 40-60 hours per week.
Yes, during the regular weeks we have office hours and labs sheets students get to follow labs and ask questions. During the project weeks, students will join the project mentoring sessions to interact the project mentors.
There are two types of projects: personal projects (also called capstone or portfolio projects) and real client projects. All students in the course will need to complete the capstone project. The real client project is a different training and career service offered at WeCloudData via our partner Beamdata. Learners will become a trainee and receive project-based training. Learners will be assigned to a real project team to work with clients and get mentored and trained by our project managers and project leads. It’s a great learning opportunity and also allow the students to gain real experience to stand out in the job market. You can talk to our learning advisors to find more details.
Yes. The Data Science Part-time Bootcamp comes with 6 months of career mentorship. During the bootcamp, we host resume workshops, interview preparation sessions and help students with their resumes and portfolio projects. After the Bootcamp, students will enter a 6-month career mentoring phase where they work with an industry mentor on a one-on-one basis for job search. Mentoring sessions are one of the most important advantage of WeCloudData’s bootcamps. It offers services beyond resume help and the mentors are all data industry professionals instead of regular career counselors.
Our career services include: resume workshop, interview workshop, industry guest lectures, job recommendation and referral, 1-1 career mentoring.
You can find our alumni reviews and stories by visiting the student success pages.
Yes. If you’re doing the bootcamp to up-skill yourself you can opt out of the career service. Fees can be deducted from the tuition.
Upon successfully completing the Bootcamp, Canadian learners will get a diploma issued by WeCloudData Academy (under Ministry of Education). Please contact our learning advisor for more details. For US and international learners, you will get a Bootcamp certificate.
Yes. Scholarship is available for students who meet the requirements. A scholarship test needs to be completed and the learner needs have a 20-minute live assessment with the program manager. Alumni who have completed courses that meet the pre-requisites will also be eligible for scholarships.
Yes. We offer flexible payment plans and work with 3rd parties to offer loans as well. Please fill out the inquiry form to access the course package page. It has the payment plan details. Or you can contact our learning advisors for more details.
View our Data Science Bootcamp (Part-Time) course package

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Data Science Bootcamp (Part-Time)

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Upcoming Events
Data & AI Career Guides – Reverse Engineer Job Search
May 23, 2024
8:00 pm -
 10:00 pm
 EST
Data Science and Generative AI as a New Career Frontier
May 28, 2024
8:00 pm -
 10:00 pm
 EST
AMA with Data Career Mentors (bring your questions)
May 30, 2024
8:00 pm -
 10:00 pm
 EST
Use OpenAI to build resume and supercharge your job search
June 4, 2024
8:00 pm -
 10:00 pm
 EST
[Lunch & Learn] AMA: careers in data for new graduates
May 23, 2024
12:30 pm -
 1:30 pm
 EST