Google Cloud : Smart Analytics, Machine Learning, and AI on Google Cloud
-
Learned to design, build, and deploy data analytics and machine learning solutions using Google Cloud’s unified data and AI ecosystem
-
Gained hands-on experience in modernizing data warehouses, running big data analytics, and applying both pre-built and custom ML models to solve business problems
-
Developed a deep understanding of the end-to-end machine learning lifecycle (MLOps) — from data preparation and training to deployment and production management
-
Applied AI-driven techniques to extract insights from structured and unstructured data, supporting smarter, data-informed decision-making
​​
Tools & Techniques:
-
BigQuery & BigQuery ML – serverless analytics and SQL-based machine learning model development
-
Vertex AI – unified MLOps platform for model building, training, deployment, and monitoring
-
Pre-built ML APIs – Google’s AI services for Vision, Natural Language, and Translation to analyse unstructured data
-
Jupyter Notebooks (Vertex AI Workbench) – interactive environment for data exploration and custom ML development
-
TensorFlow / Keras – frameworks for building and fine-tuning advanced machine learning models
-
Production ML Pipelines – automated workflows for model training, evaluation, and deployment
-
Data Analysis & AI Fundamentals – understanding key AI and ML concepts in business analytics applications