GCP - Google Cloud Professional Data Engineer Certification
Learn Google Cloud Professional Data Engineer Certification with 80+ Hands-on demo on storage, Database, ML GCP Services
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Udemy Coupon Code for GCP – Google Cloud Professional Data Engineer Certification Course. Learn Google Cloud Professional Data Engineer Certification with 80+ Hands-on demo on storage, Database, ML GCP Services
Created by Ankit Mistry, GCP Certification – Google Cloud Academy | Associate Cloud & Professional Engineer Certifications | 23.5 hours on-demand video course
Google Cloud Professional Data Engineer Course Overview
Online Course: GCP – Google Cloud Professional Data Engineer Certification from Udemy
Google Cloud Platform GCP is Fastest growing Public cloud. PDE (Professional Cloud Data Engineer) certification is the one which help to deploy Data Pipeline inside GCP cloud. This course has 16+ Hours of insanely great video content with 80+ hands-on Lab (Most Practical Course)
Google Cloud : Professional Cloud Data Engineer Certification is the best to invest time and energy to scale your data storage & processing demand. I am all exited to help you on your journey towards Google Cloud Professional Cloud Data Engineer Certification. So, I created most practical comprehensive course will prepare you for Professional Cloud Data Engineer certification, having 16+ hours of HD quality video content.
Major Theme of this Certification Course
1. Data Engineering & GCP Basic Services
In this module I will Start with Data engineering pipeline,
Different Types of data : structure data, semi-structured data, unstructured data, some concept related to batch data processing and stream data GCP related concepts like GCP region and Zones, how to create a GCP account & various GCP service being offered from the data engineering perspective.
Then we’ll see about GCP basic infrastructure services like IAM, VM, kubernetes provisioning, app engine, cloud run and cloud function deployment.
2. Data Storage in GCP
In this module I will teach you different Data storage product for storing unstructured data, Google cloud storage, file Store, persistent disk storage, local SSD storage and how to do data migration from on-premise to GCP.
3. Database Offering by GCP
In this module I will teach you Database solution for storing structured data & semi-structured data.
- For storing structured data inside GCP we have a Google cloud SQL and a cloud spanner is available.
- For semi-structured data inside the GCP we have a Google cloud BigTable, DataStore/firestore and for in memory power MemoryStore available
4. Data Processing in GCP
In This Data processing section we will begin with Data warehousing analytical data processing solution google cloud BigQuery and for asynchronous communication we will see Google cloud PubSub services.
For developing complete pipeline inside GCP –
- Dataflow Apache beam solution inside Google cloud
- Google cloud DataProc for lift and shift Hadoop and Spark job
- Without writing code with just drag and drop build complete pipeline with cloud Data fusion
- Monitor Author and schedule a complete workflow we have a Apache airflow – Cloud Composer is available
- For sensitive and personally identifiable data detection Data loss prevention API – DLP
- Search for or all data set at one single place Data Catalog is available
5. ML/AI offering in GCP
In this module we will begin with basics of Machine learning
Prepare your data with intelligent data preparation tool Dataprep before throwing all your data to a machine learning algorithm
We will see different pre-built machine learning API for vision, language and speech
Double auto machine learning model with AutoML
Building custom machine learning model with various framework life tensorflow, scikit learn and Pytorch
Bigquery ML for machine learning training with SQL
At the end we will see how to create beautiful reports and visualization with in browser Google cloud data studio tool
What you’ll learn
- Grasp Basic Data Engineering & Database Concept
- Provision Basic GCP infrastructure services – VM, Container, GKE, GAE, Cloud Run
- Learn Various Storage Product like Cloud Storage, Disk, Filestore for Unstructured Data
- Structure Data Solution – SQL, Spanner, BigQuery
- Store massive semi structure data in BigTable, Datastore
- Deploy Data Pipeline on different Data Processing Product – DataFlow (Apache Beam), DataProc (Hadoop/Spark), Data Fusion, Composer(Airflow)
- Cleanse, Wrangle & Prepare Your Data with DataPrep
- Machine Learning Basics & its GCP Solution Product
- Search Data Asset from Data catalog
- Visualize Data by creating Reports & Dashboard with Google Data Studio
- Use Prebuilt ML API (Vision, Language, Speech) in your application
- Apply Auto ML on your own data to build model
- Build Machine Learning Custom Model with Notebook , Scikit Learn Library
- Deploy Scikit-learn Model, Tensorflow as endpoint for prediction
- Detect Sensitive PII data with Data Loss Prevention (DLP) API
- Store process and analyse your petabyte-scale data with Google data warehousing solution cloud bigquery
- Decouple application with asynchronous communication Google cloud pub sub
- Store data inside the memory for faster access with memory Store redis database
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Who this course is for:
- Cloud Engineer who want to get certified in Google cloud Data Engineer
- Anyone looking to use Google cloud for Data Pipeline in Organization
- Data Engineer who want to learn various GCP products for Data Engineering
- Anyone who want to learn about various Storage & Database Product for Storing Data
- Anyone who want deploy ML Model/ Data Pipeline on Google Cloud
Taught by Ankit Mistry