Google Certified Professional – Data Engineer OnlineTraining in Karachi, Lahore, Islamabad, Pakistan, Dubai

Google Certified Professional – Data Engineer

A Professional Data Engineer gathers, transforms, and publishes data to make data-driven decisions. With security and compliance, scalability and efficiency, fidelity and dependability, adaptability, and portability in mind, a data engineer should be able to design, construct, operationalize, secure, and monitor data processing systems. They should also be able to use, deploy, and constantly train pre-existing machine learning models. The need for data engineers is constantly growing and certified data engineers are some of the top paid certified professionals. Data engineers have a wide range of skills including the ability to design systems to ingest large volumes of data, store data cost-effectively, and efficiently process and analyze data with tools ranging from reporting and visualization to machine learning.

Course Key Learnings

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

Course Outline

Module 1Data Engineering & GCP Basic Services

In this module you 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.

Module2. Data Storage in GCP

In this module you will learn 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.

Module3. Database Offering by GCP

In this module you will learn

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.

Module4. 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

Module5. 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 AutoMLBuilding custom machine learning model with various framework life tensorflow, scikit learn and Pytorch

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

Prerequisites:
A good understanding of computer science, software engineering, data engineering, and machine learning technology
Familiarity with GCP fundamentals, such as cloud networking, regions, identity and access management (IAM)

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International Student Fee: 500 USD

Flexible Class Options