retrieval-augmented generation (RAG) pipelines, Customer Journey Analytics (CJA), Adobe Analytics, Sql, Numpy, Pandas, Databricks, Clustering, Python, experimentation design, statistical significance, statistical forecasting models, Powerpoint, a/b testing, cloud-based data lakehouse platforms, Regression, chatbots, prompt-engineered tools, AI agents, LLM-based applications

Natural Language Processing, Deep Learning, MLops, Gcp, Docker, Kubernetes, Python, LangChain, CPLEX, reinforcement learning, BigQuery ML, Mixed-Integer Programming, Vertex AI, LlamaIndex, Gurobi, Linear Programming

record linkage , Numpy, Nlp, Docker, XGBoost, Flask, Python, Sql, Pandas, FastAPI, embeddings, scikit-learn, fuzzy matching, Levenshtein, model evaluation, RAG fundamentals, LLM GenAI, sentence-transformers, model deployment, entity resolution, prompt engineering, Jaro-Winkler, REST API serving, vector similarity search, text embeddings

Machine Learning, Data Visualization, Python, Deep Learning, AIML

Tensorflow, Sql, Apache Spark, Pyspark, Kafka, MLops, Pytorch, Kubernetes, Python, Docker, Scala, XGBoost, LightGBM

Nlp, Gcp, MLops, Docker, PostgreSQL, Elasticsearch, Elk Stack, Azure, Python, AWS, Generative AI

probability , Sql, Power Bi, Python, MATLAB, Tableau, Machine Learning, R, Statistics, metrics design

Sql, Tensorflow, Pandas, Python Programming, Numpy, Pytorch, Scipy, LLMs, model deployment workflows, scikit-learn, statsmodels, vector databases, GenAI technologies, RAG, LangChain, MLOps practices, prompt engineering