Course curriculum
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1
Welcome!
- About this course: AWS Certified Solutions Architect Certification Program
- Key pointers for success in this course
- Curriculum Description
- Instructor Bio: Charlie Crawford
- Instructor Bio: Mark Kerzner
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2
Program Announcements and notifications
- Announcement 001 - Instructions for storing labs, etc.
- Announcement 002 - Slack Channel Notification
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3
Calendar, Discussion Forum and More
- Course Calendar
- Schedule: Live Instruction and Office Hours (Version 2.0 as of Feb 25, 2019)
- Slack Channel / Discussion Forum (All announcements, Q&A with instructors, etc.)
- If (and when) you need help...
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4
Labs
- Labs - Overview
- INSTRUCTIONS: Virtual labs (For Colaboratory)
- INSTRUCTIONS: Lab Uploads to TCS servers
- Week 1: Labs
- Week 2: Labs
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5
Recordings (of Live Instruction and Office Hours)
- RECORDING: Office Hours - Week 1, Session 1
- RECORDING: Live Instruction Week 1, Session 1
- RECORDING: Office Hours - Week 1, Session 2
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6
Week 1
- Week 1 - Focus and Objectives
- READING: Intro to Machine Learning for Managers (Read Pages 1-12)
- READING: TCS - Machine First Approach (Read all)
- READING: TCS Global Trend Study - AI Overview (Skim all)
- READING: Jeff Dean Rice Talk - State of Artificial Intelligence (Read entire document) (Dated but useful)
- Lesson 1: Introduction to Machine Learning
- Lesson 1: Lab 1
- Lesson 2-1: Pandas
- Lesson 2-1: Exploring Pandas
- Lesson 2-1: Lab-2a
- Lesson 2-2: Lab-2b
- Lesson 2-2: Lab 2c
- Lesson 2-3: Visualization (only 1 part for this; "Part 2" is deleted now)
- Lesson 2-4: Visualization-Stats
- Lesson 2-4: Lab-2d
- Lesson 3-1: Sklearn
- Lesson 3-2: Lab-3b
- Lesson 3-2: Linear Regression
- Lesson 3-3: Multivariate Linear Regression
- Lesson 3-4: Logistic Regression (with fixed audio)
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7
Week 2
- Week 2 - Focus and Objectives
- READING: ISLR (Read Chapter 8 - Trees)
- READING: ISLR (Read Chapter 9 - Support Vector Machine)
- READING: ISLR (Read Chapter 10 - Unsupervised)
- Lesson 1a: Classification (Support Vector Machines)
- Lesson 1b: Classification (Naive Bayes)
- Lesson 2a: Decision Trees
- Lesson 2b: Random Forests
- Lesson 3a: Clustering
- Lesson 3b: Principal Component Analysis
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8
Week 3
- Week 3 - Focus and Objectives
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9
Week 4
- Week 4 - Focus and Objectives
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10
Week 5
- Week 5 - Focus and Objectives
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11
Week 6
- Week 6 - Focus and Objectives
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12
Final Examination
- FINAL EXAM - BC
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13
AWS Immersion Primer
- AWS Immersion Part 1 - Overview
- AWS Immersion Part 2 - EC2 Demo
- AWS Immersion Part 2 - Foundation Services
- AWS Immersion Part 2 - Foundation Services Continued
- AWS Immersion Part 3 - Security Overview
- AWS Immersion Part 4 - S3 Demo
- AWS Immersion Part 4 - Security Best Practices
- AWS Immersion Part 4 - Security Best Practices Continued
- AWS Immersion Part 5 - Databases on AWS
- AWS Immersion Part 6 - Messaging Services
- AWS Immersion Part 7 - High Availability
- AWS Immersion Part 8 - Serverless Architectures
- AWS Immersion Part 9 - Migration Strategies Continued
- AWS Immersion Part 9 - Migration Strategies
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14
AWS Deep Dive
- AWS DEEP DIVE - 02 IDENTITY AND ACCESS MANAGEMENT
- AWS DEEP DIVE - 02 IDENTITY AND ACCESS MANAGEMENT
- AWS DEEP DIVE - 04 SET UP AWS CREDENTIALS
- AWS DEEP DIVE - 05 USING S3 FOR STORAGE
- AWS DEEP DIVE - 09 AMAZON MACHINE IMAGE
- AWS DEEP DIVE - 10 ELASTIC BLOCK STORAGE
- AWS DEEP DIVE - 11 ELASTIC BLOCK STORAGE DETAIL
- AWS DEEP DIVE - 12 INSTANCE STORAGE
- AWS DEEP DIVE - 13 INSTANCE STORAGE 2
- AWS DEEP DIVE - 17 AUTOSCALING
- AWS DEEP DIVE - 18 CUSTOM AMIS
- AWS DEEP DIVE - 19 ELASTIC LOAD BALANCING
- AWS DEEP DIVE - 20 ELASTIC LOAD BALANCING - DEMO
- AWS DEEP DIVE - 21 AUTOSCALING LAUNCH CONFIGURATION
- AWS DEEP DIVE - 24 SUMMARY