Data Science - Basic, Machine Learning, Technology, AI-Data science

Pyspark, Apache Hadoop, Machine Learning, Apache Spark, Sql, Devops, Data Science, Numpy, Pandas, Powerbi, Agile, Cloudera, Databricks, Azure, Rapidminer, Python, Big data frameworks, Scikitlearn

attribution , snowflake , BigQuery, Data Quality, Data Modeling, Sql, Spark, Databricks, Python, AI-assisted troubleshooting, ML-driven systems, campaign optimization, Trino, experimentation, RTB bidding, Data pipelines

Excel, Sql, Logistic Regression, Time Series, Clustering, Kubernetes, Decision Trees, Feature selection, Boosting, Regularization techniques, Regression, Statistical Techniques

Pandas, Spark, Python, Tuning the models, Tuning of Data, Lang Chain, Data frames, Core Data science skills, Gen AI, anomaly detection, Agentic AI, Product configuration, RAG, Azure AI, data models

Aws Lambda, Machine Learning, Uipath, AWS Glue, AWS Athena, Sql, Python, Aws S3, GenAI, AWS Bedrock, n8n, Claude Code, OpenAI Codex, AWS Kiro, GitHub Copilot

Numpy, Scipy, Pandas, Apache Spark, Databricks, Python, scikit-learn, Jupyter

Apache Hadoop, Powerbi, Pyspark, Apache Spark, Cloudera, Databricks, Rapidminer, Python, Sql

Performance Tuning, Data Governance, Databricks, AWS, Data Analysis, model training, Monitoring, analytics pipelines, cloud-native AWS services, Analytics, recommendation models, data ingestion, Databricks Spark, feature engineering, security standards, refinement