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Data Science Bootcamp (Vancouver)
Applied Data Science and Big Data Diploma Program

18-week immersive learning program designed for university/college graduates and career switchers in the industry who want to learn data science skills fast, gain real hands-on industry experience, and get a job in the Data & AI industry in a relatively short time frame.

At a Glance
Intermediate
What you will learn

You will learn essential data science skills in the classroom, practice what you learn on real projects, gain critical experience, and learn from your industry mentors during the job search phase.

Summary
18 weeks
576 hours
Project-based Learning
Learn through hands-on experiences
Expert Instructors
Experienced and knowledgable instructors

Full-time

18 weeks

Online Live, On Campus

Applied Data Science

About the Program

The Applied Data Science and Big Data Diploma Program is created to help close the gap between Academia and the Industry. It is a 6-month immersive learning program designed for university/college graduates and career switchers in the industry who want to learn data science skills fast, gain real hands-on industry experience, and get a job in the Data & AI industry in a relatively short time frame.

WHO SHOULD CONSIDER THIS DIPLOMA PROGRAM?
  • University/college graduates in any fields
  • Career switchers in the industry who are looking for a smooth transition
  • Job seekers who want a systematic approach to polish DS skills and project portfolios
  • Masters/PhDs who lack industry experience

Career Occupations

Most of our graduates from this program will get hired for jobs with the following titles:

  • Data Scientist
  • Data Analyst
  • Data Engineer
Our alumni are working at

What you will learn

  • Qualify to become a SQL master and be familiar with RDBMS and NoSQL Technologies
  • Learn to become a python coder and go beyond Jupyter Notebook
  • Master data munging and preparation skills using Pandas DataFrame and SQL
  • Be skilled at data exploration using Python packages such as Matplotlib, Seaborn, Folium, Plotly, and build Plotly or Tableau Dashboards like a pro
  • Acquire enough calculus, linear algebra, and statistics knowledge for machine learning
  • Master machine learning theory and common packages such as Scikit-learn, Keras, NLTK and
  • Understand how to build an end-to-end machine learning project
  • Gain hands-on experience with leading big data platforms such as Apache Spark, Databricks, AWS SageMaker, and Hadoop

CURRICULUM

PROGRAM ORGANIZATION
Title of Course/Work Experience Component

Applied Deep Learning
Applied Machine Learning 
Big Data Analytics
Business Presentations & Public Speaking
Data Science Capstone
Data Science Toolbox
Data Visualization
Python for Science

TOTAL HOURS
TOTAL WEEKS
# of Hours

48
96
96
32
72
72
64
96

576 hours
18 weeks

Course Materials

  • Deep Learning Publisher: The MIT Press (Nov. 18
    2016) ISBN-10: 0262035618
  • The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition Publisher: Springer; 2nd ed. 2009, Corr. 9th printing 2017 edition (April 21 2017) ISBN-10: 0387848576
  • OpenIntro Statistics: Third Edition Publisher: OpenIntro, Inc.; 3 edition (July 2 2015) ISBN-10: 194345003X
  • Hadoop: The Definitive Guide Paperback: 688 pages Publisher: Yahoo Press; Language: English ISBN-10: 9781449311520
  • Learning Spark: Lightning-Fast Big Data Analysis Paperback: 276 pages Publisher: O’Reilly Media Language: English ISBN-10: 1449358624
  • Mastering Apache Cassandra – Second Edition Paperback: 350 pages Publisher: Packt Publishing Language: English ISBN-10: 9781784392611
  • The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition Publisher: Springer; 2nd ed. 2009, Corr. 9th
    printing 2017 edition (April 21 2017) ISBN-10: 0387848576
  • OpenIntro Statistics: Third Edition Publisher: OpenIntro, Inc.; 3 edition (July 2 2015) ISBN-10: 194345003X
  • Learning SQL: Master SQL Fundamentals Publisher: O’Reilly Media; Second Edition,Annotated edition (April 30 2009) ISBN- 10: 0596520832
  • Learn Python The Hard Way Publisher: Addison- Wesley Professional; 3 edition (Oct. 1 2013) ISBN-10: 0321884914
  • Effective Data Visualization: The Right Chart for the Right Data Sage Publications; 1 edition (May 18 2016) ISBN-10: 1506303056
  • Python Data Science Handbook: Essential Tools for Working with Data Paperback: 548 pages Publisher: O’Reilly Media; 1 edition (Dec 10 2016)
    Language: English ISBN-10: 149191205

Admission Process

  1. Provide the College with a transcript evidencing the student has graduated from an undergraduate degree program.
    OR
    Provide the College with a resume showing the student has a minimum of five years’ industry experience.
  2. Must complete an Admissions Interview.

For International students or students whose first language is not English, in addition to the admission requirements listed above, the student must also meet one or more of the following language proficiency requirements:

  • Provide evidence the student has completed a Test of English as a Foreign Language (TOEFL) with a minimum score of CBT 213 OR iBT 78;
  • Provide evidence the student has completed an International English Language Testing System (IELTS) with a minimum score of 6.0
  • Provide evidence the student has completed a Canadian English Language Proficiency Index Program (CELPIP) – General Test with a minimum score of 7.0
  • Provide evidence the student has completed a Test of English for International Communication (TOEIC) with a minimum score of 780
  • Provide evidence the student has successfully completed grade 12 or post-secondary education in an English instructional school system.

 

In addition, all international students are required to obtain a valid study visa to complete the Program

Schedule, Tuition & Financing Options
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