GCP 자격에 부끄럽지 않은 실무 능력을 갖추기 위하여, LAB 중심의 실무 강좌를 다음과 같이 준비 하였습니다.
먼저 LAB 메뉴얼을 업데이트 하겠습니다. (동영상 강좌 추후 추가 예정)
| No. | 내용 | 완료일 |
| 1 | Explore a BigQuery Public Dataset | 2019-09-19 |
| 2 | Recommend Products using ML with Cloud SQL and Dataproc | 2019-09-19 |
| 3 | Predict Visitor Purchases with a Classification Model with BigQuery ML | 2019-09-19 |
| 4 | Create a Streaming Data Pipeline for a Real-Time Dashboard with Cloud Dataflow | 2019-09-19 |
| 5 | Classify Images with Pre-built ML Models using Cloud Vision API and AutoML | 2019-09-20 |
| 6 | Create a Dataproc Cluster | 2019-09-20 |
| 7 | Work with structured and semi-structured data | 2019-09-20 |
| 8 | Submit Dataproc jobs for unstructured data | 2019-09-20 |
| 9 | Leveraging Unstructured Data | 2019-09-20 |
| 10 | Cluster automation using CLI | 2019-09-20 |
| 11 | Add Machine Learning | 2019-09-20 |
| 12 | Building a BigQuery Query | 2019-09-23 |
| 13 | Loading and Exporting Data | 2019-09-23 |
| 14 | Advanced SQL Queries | 2019-09-23 |
| 15 | A Simple Dataflow Pipeline (Python) | 2019-09-23 |
| 16 | MapReduce in (Python) | 2019-09-23 |
| 17 | Side Inputs (Python) | 2019-09-23 |
| 18 | Explore dataset, create ML datasets, create benchmark | 2019-09-23 |
| 19 | Getting Started with TensorFlow | 2019-09-23 |
| 20 | Machine Learning using tf.estimator | 2019-09-23 |
| 21 | Refactoring to add batching and feature-creation | 2019-09-23 |
| 22 | Distributed training and monitoring | 2019-09-23 |
| 23 | Scaling up ML using Cloud ML Engine | 2019-09-23 |
| 24 | Feature Engineering | 2019-09-23 |
| 25 | Publish streaming data into Pub/Sub | 2019-09-23 |
| 26 | Streaming Data Pipelines | 2019-09-23 |
| 27 | Streaming Analytics and Dashboards | 2019-09-23 |
| 28 | Streaming data into Bigtable | 2019-09-23 |
Course Features
- Lectures 30
- Quizzes 17
- Duration 40 hours
- Skill level All levels
- Language Korean
- Students 19
- Certificate No
- Assessments Self
- 3 Sections
- 30 Lessons
- 24 Weeks
Expand all sectionsCollapse all sections
- 사전준비1
- Contents45
- 2.1Explore a BigQuery Public Dataset30 Minutes
- 2.2Check 0110 Minutes1 Question
- 2.3Recommend Products using ML with Cloud SQL and Dataproc60 Minutes
- 2.4Check 0210 Minutes1 Question
- 2.5Predict Visitor Purchases with a Classification Model with BigQuery ML60 Minutes
- 2.6Check 0310 Minutes1 Question
- 2.7Create a Streaming Data Pipeline for a Real-Time Dashboard with Cloud Dataflow60 Minutes
- 2.8Check 0410 Minutes1 Question
- 2.9Classify Images with Pre-built ML Models using Cloud Vision API and AutoML60 Minutes
- 2.10Check 0510 Minutes1 Question
- 2.11Create a Dataproc Cluster30 Minutes
- 2.12Check 0610 Minutes1 Question
- 2.13Work with structured and semi-structured data60 Minutes
- 2.14Check 0710 Minutes1 Question
- 2.15Submit Dataproc jobs for unstructured data60 Minutes
- 2.16Check 0810 Minutes1 Question
- 2.17Leveraging Unstructured Data60 Minutes
- 2.18Check 0910 Minutes1 Question
- 2.19Cluster automation using CLI60 Minutes
- 2.20Check 1010 Minutes1 Question
- 2.21Add Machine Learning60 Minutes
- 2.22Check 1110 Minutes1 Question
- 2.23Building a BigQuery Query60 Minutes
- 2.24Check 1210 Minutes1 Question
- 2.25Loading and Exporting Data60 Minutes
- 2.26Check 1310 Minutes1 Question
- 2.27Advanced SQL Queries60 Minutes
- 2.28Check 1410 Minutes1 Question
- 2.29A Simple Dataflow Pipeline (Python)60 Minutes
- 2.30Check 1510 Minutes1 Question
- 2.31MapReduce in (Python)60 Minutes
- 2.32Check 1610 Minutes1 Question
- 2.33Side Inputs (Python)60 Minutes
- 2.34Check 1710 Minutes1 Question
- 2.35Explore dataset, create ML datasets, create benchmark60 Minutes
- 2.36Getting Started with TensorFlow60 Minutes
- 2.37Machine Learning using tf.estimator60 Minutes
- 2.38Refactoring to add batching and feature-creation60 Minutes
- 2.39Distributed training and monitoring60 Minutes
- 2.40Scaling up ML using Cloud ML Engine60 Minutes
- 2.41Feature Engineering60 Minutes
- 2.42Publish streaming data into Pub/Sub60 Minutes
- 2.43Streaming Data Pipelines60 Minutes
- 2.44Streaming Analytics and Dashboards60 Minutes
- 2.45Streaming data into Bigtable60 Minutes
- Survey1
