[Udemy, Ankit Mistry] GCP - Google Cloud Professional Data Engineer Certification [1/2025, ENG]

Some Feedback about course from STUDENTS:

5 ⭐- Recommended ankits all GCP certification course. all are very much comprehensive & fully practical course.
5 ⭐- great overview of all topics, highly recommended course
good explaination of the various data services
5 ⭐- One of the awesome GCP data engineer course i have ever watched, learned a lot, Thank you @ankit Mistry.
5 ⭐- The instructor gives very detailed and easy-to-understand explanations. In addition, he explores the theoretical concepts inside the Google Cloud Console. So, it's very practical, as well. I highly recommened.
5 ⭐- Good course with lots of practical work to follow along and learn from.

Have a look at course curriculum, to see depth of Course coverage:

Major Theme of this certification course are:
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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.
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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.
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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

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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

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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

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