Description
Boot Camp Name: How to Prepare, Get, and Succeed in a Software/Machine Learning Engineer Job at Big Tech Companies
Introduction:
You might hear that FANG (Facebook, Amazon, Apple, Netflix, and Google) pays $140k+ annual compensation for an entry level Software/Machine Learning Engineer. In this boot camp, we will teach you the time-efficient learning path, learning materials, approaches, and key starting knowledge to prepare and get a Software/Machine Learning Engineer Job at FANG. The goal of this boot camp is to help you get a Software/Machine Learning Engineer job after 3-6 months of guided time-efficient hard work and be ready to get a FANG job in 1-2 years.
Instructor: Leo Ying, Ph.D.
Dr. Ying is the president of AlbertaAI. He has over 15 years of professional experience in software engineering, entrepreneurship, AI, and enterprise architecture in China and Canada. He is also a mentor in the Multimedia Research Centre at the University of Alberta and has taught 150+ Multimedia Master Program students on Deep Learning and Computer Vision since 2016. Many of his students become software or machine learning engineers in Amazon, Microsoft, or further pursue Ph.D. or start his/her own companies.
Registration Link: [TO BE ADDED]
Contents:
Step 1: Learning Approaches and Mindset
- Learning approaches (how to search, select learning materials, practice, and accumulate project experiences)
- Build self-learning/motivated mindset
- How to master computer engineering
- How to be more efficient on learning
- How to troubleshoot
Step 2: Master in Python
- How to learn and be proficient in Python (if you haven’t)
- Data Structures
- Libraries
- Algorithms
- Most important things you should master in Python
Step 3: Master in Machine Learning, Neural Network, Pytorch, Data Engineering
- How to learn machine learning, neural network, Pytorch
- Key concepts in Machine Learning
- Key concepts in Neural Network
- Key concepts in Pytorch
- Key concepts in Computer Vision
- Key concepts in Data Engineering
Step 4: Accumulate Project Experiences
- How to accumulate project experiences
- Selected online tutorials
- Selected Kaggle Competitions
- How to start your own Personal projects
- How to start your own startup team and project
Step 5: Find Jobs
- Hiring process: recruiter outreach, code test, hiring manager phone call, onsite interview
- How to polish your resume and LinkedIn
- How to use angel.co to list your profile and find software / machine learning engineer jobs
- How to prepare Leetcode and HackerRank
- How to behaviour in interviews
- How to prepare most interviewed algorithms
- How to prepare problem solving interviews
- How to negotiate salaries and compensation
Step 6: Leadership at Workplace
- Build a leadership mindset
- Hardworking, Confident, Fast-learning
- Humble, Warm hearted, Share
- How to succeed in your job
- Proactive, Responsive communication
- Do your due diligence and ask smart questions
- Professional
- Put yourself in others shoe
Highlights:
- Earn a shareable certificate if passing final exam
- No prior experience required
- Reference support
- Help on Troubleshooting
- Career mentorship
- Join and connect with the local AI community
- Access to course recording, no worries if you need to miss a day
- Study anywhere through Zoom
Audience: Who targets to find a job in big tech companies (e.g. FANG)
Prerequisites: major in engineering / science or familiar with coding
Required Commitment: 3 hours for lecture + 6 hours for assignments every week
Skill Level: Beginner / Intermediate
Location: Online (Zoom Meeting link will be sent by email after registration)
Language: English
Tuition Fee: $400 for one student and $600 for two students together
Organizers: Zerobox, Alberta Artificial Intelligence Association (AlbertaAI www.albertaai.org)
Certificate: You will receive a certificate from Zerobox and AlbertaAI if you pass the final evaluation (need to use the same name for registration and certificate)
Requirement: Use your own personal computer for this boot camp
Date & Time:
| Class ID | Date | Time |
| 2022-1 | Jan 8-29, 2022 | Saturdays, 9am-12pm MT |
