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Bootcamp Programs

Launch your career in Data and AI through our bootcamp programs

  • Industry-leading curriculum
  • Real portfolio/industry projects
  • Career support program
  • Both Full-time & Part-time options.
Data Science & Big Data

Become a data engineer by learning how to build end-to-end data pipelines

 

Become a data analyst through building hands-on data/business use cases

Become an AI/ML engineer by getting specialized in deep learning, computer vision, NLP, and MLOps

Become a DevOps Engineer by learning AWS, Docker, Kubernetes, IaaS, IaC (Terraform), and CI/CD

Short Courses

Improve your data & AI skills through self-paced and instructor-led courses

  • Industry-leading curriculum
  • Portfolio projects
  • Part-time flexible schedule
AI ENGINEERING
Portfolio Courses

Learn to build impressive data/AI portfolio projects that get you hired

  • Portfolio project workshops
  • Work on real industry data & AI project
  • Job readiness assessment
  • Career support & job referrals

Build data strategies and solve ML challenges for real clients

Help real clients build BI dashboard and tell data stories

Build end to end data pipelines in the cloud for real clients

Location

Choose to learn at your comfort home or at one of our campuses

Corporate Partners

We’ve partnered with many companies on corporate upskilling, branding events, talent acquisition, as well as consulting services.

AI/Data Transformations with our customized and proven curriculum

Do you need expert help on data strategies and project implementations? 

Hire Data, AI, and Engineering talents from WeCloudData

Our Students

Meet our amazing alumni working in the Data industry

Read our students’ stories on how WeCloudData have transformed their career

Resources

Check out our events and blog posts to learn and connect with like-minded professionals working in the industry

Read blogs and updates from our community and alumni

Explore different Data Science career paths and how to get started

Our free open source courses and workshops gives you the skills and knowledge needed to transform your career in tech

Data Science
Big Data for Data Scientists

The amount of structured and unstructured data is exploding at a phenomenal speed. Python and R are NOT the best tools when it comes to analyzing big data.

As more and more companies move to build their data infrastructure in the cloud, new distributed computing frameworks such as Hadoop and Spark emerged as distributed platforms. Data Scientists who analyze big data not only need to adapt these new tools but also need to deeply understand the data infrastructures, database systems, as well as how to build data science pipelines in the Cloud platforms such as AWS and Azure.

So you have seen big data-related keywords mentioned countless times in data scientist job descriptions but don’t know how to get started? Have you learned big data theory from Udemy or Udacity but still don’t know how to apply the big data tools to complete a complex project from end to end?

Fill out the inquiry form to learn about the course curriculum or talk to our learning advisor.

WeCloudData Best Data Science Bootcamp - Switchup
At a Glance
Advanced
What you will learn

This advanced-level big data course teaches you the practical big data skills that you won’t be able to learn anywhere else. It covers several important topics such as distributed computing, cloud, real-time data ingestion, machine learning at scale, as well as how to deploy and operationalize machine learning models in production.

Summary
Gain competitive advantage in job market
Learn how to architect big data pipelines
Daily TA office hours
Build end-to-end big data project

Part-time

Online Live

8 weeks

About the Program

Big Data for Data Scientists is an 8-week advanced-level project-based course that teaches data scientists the necessary tools to work on large-scale data science problems. The entire course is built around an end-to-end real-time machine learning problem. Students will learn the most cutting-edge big data frameworks and tools such as Apache Spark, Amazon SageMaker, Databricks, MLflow, Kafka, Elasticsearch, and Airflow. Students will also learn how to train machine learning models at scale and deploy models at scale in real-time.

for those who want to
  • Acquire big data skills to handle large data problems
  • Focus on MLOps, Big Data, and Model Deployment on AWS
  • Build end-to-end big data and machine learning projects to enhance and elevate your data science portfolio
  • Enhance your knowledge of machine learning and big data at scale

Speak to our advisor

Our Program Advisor can answer all your questions and help you pick a program that best suits your need. Please fill in your information below and we will contact you.

You can also contact us at info@weclouddata.com or (647) 588-4206

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What you will learn

  • Be enterprise ready!
    Only know the textbook definition of big data? In this course, students will get familiar with enterprise data architecture and pipelines in several industries. It gives the students a clear picture of where big data fits in and how it can work along with the traditional enterprise data architecture.
    • Enterprise data flow in retail, banking, telecommunications
    • Data lake vs Traditional EDW
  • Master important big data analytics tools
    Whether you are tasked with using Hive to run ETL jobs, Presto/Athena as the query engine to build BI dashboards, or Elasticsearch database to query log files, this module covers the essential tools and you will learn not only how to write queries but also when to use each tool.
    • Batch jobs with Apache Hive
    • SQL on Hadoop with Presto and Amazon Athena
    • Full-text and log queries with Elasticsearch
    • Build real-time dashboards using Kibana and Superset
  • Master Apache Spark for Big Data
    Master Apache Spark for Big Data
    • Work with low-level Spark RDD API for maximum flexibility
    • Use Spark DataFrame for ETL, data transformations and preparation
    • Write Pandas UDF to optimize Spark DataFrame operations
    • Understand Spark DataFrame internals and query optimizations
    • Learn Spark Structured Streaming to process near-real-time streaming data
    • Learn the latest Kaolas API
  • Machine Learning at Scale with Spark
    Want to parallelize your scikit-learn jobs in Spark? Want to learn how to distribute parameter tunings? Want to learn how to train machine learning models on large datasets? This module covers Spark's Machine Learning API.
    • Spark ML for Supervised Learning
    • Spark ML for Unsupervised Learning
    • Collaborative Filtering with ALS
    • Model Persistent with Spark ML, MLleap, JPMML
  • AWS MLOps with SageMaker
    Amazon announced several exciting SageMaker features in the 2019 Re:Invent conference. We can't wait to include those in this course. This module teaches students how to leverage Amazon SageMaker to develop, train, scale, and deploy machine learning models in production.
    • Collecting labels for ML with SageMaker Ground Truth
    • Develop ML models using SageMaker Studio
    • Train ML models and Tune parameters at scale using SageMaker
    • Advanced Feature: Bring your own containerized models
    • Deploy SageMaker models in batch and prediction services
  • Model in Production with Databricks, Docker, and MLflow
    This module teaches students how to use MLflow and Spark on Databricks to deploy spark ML models and if your company has multiple ML frameworks on multi-clouds, MLflow is a great tool to deploy and manage your models.
    • Dockerize your Sklearn/Tensorflow models
    • Deploy your own model in SageMaker
    • Model management with MLflow

Resources

Watch our recorded webinar and learn more about Data Science career and industry insights.
Why WeCloudData?
Learning Experience: Student Journey
Meet Your Faculty: Tanya Zhou
Meet Your Faculty: David Tian

Instructors & Guest Speakers

Online Learning Platform

Learn anywhere, anytime

Track your learning journey
Watch lecture recordings, work on coding challenges, ask for TA help, and get resume and job support. The learning portal allows you to track your entire learning journey with ease.
Sharpen your coding skills
Leverage our online coding tool to test your knowledge, identify your weaknesses, and improve your Python and SQL coding skills. The LeetCode style live coding challenges will help you get prepared for technical job interviews.

PORTFOLIO PROJECTS

Connect all the dots by implementing an awesome big data project
There’s nothing textbook about our approach at WeCloudData. After learning so many tools and frameworks, it’s important to know how to put everything together through an end-to-end project implementation.
End-to-End Real-Time Project (Fraud Detection)
  • Build an end-to-end real-time fraud detection pipeline using AWS, Kafka, Hive, Presto, Spark ML, Spark Streaming, Elasticsearch, and MLflow on Databricks
  • Deploy the app in AWS
  • Add the project to your big data portfolio
  • Get referred to WeCloudData's hiring network upon completing the project
PAST STUDENT PROJECTS
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weclouddata big data course student project demo 2
weclouddata big data course student project demo 3
WeCloudData big data course project real-time pipeline architecture
WeCloudData big data course student project 9
WeCloudData big data course student project 10
WeCloudData big data course student project 11
WeCloudData big data course student project 12
WeCloudData big data course student project 13
WeCloudData big data course student project 14

Reviews

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Schedule, Tuition & Financing Options

resources

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Portfolio Course

Data Science Client Project (Career Mentorship)

View our Big Data for Data Scientists course package
View our Big Data for Data Scientists course package

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