My Certificates

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Google Advanced Data Analytics Professional Certificate

Validates expertise in high-level data analysis, focusing on statistical analysis, predictive modeling, and data automation using Python.

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Google Cloud Data Analytics Professional Certificate

Focuses on processing, analyzing, and visualizing large datasets at scale using Google Cloud Platform (GCP) services like BigQuery and Looker.

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Associate Data Engineer in Databricks

Certifies proficiency in building data pipelines, engineering scalable data architectures, and optimizing data processing using Apache Spark and the Databricks Lakehouse platform.

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Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

Covers the design, deployment, and operationalization of robust data processing systems, data structures, and machine learning models on GCP.

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machine learning specialization

A foundational program covering core machine learning concepts, including supervised learning (regression, classification), unsupervised learning, and neural networks using TensorFlow.

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AI Infrastructure and Operations Fundamentals – NVIDIA

Explored the foundational technologies behind running AI at scale, including data pipelines, model deployment, and AI infrastructure. Developed an understanding of GPU acceleration, MLOps, and real-world enterprise AI systems.

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Python for Data Science, AI & Development – IBM

A foundational course in Python programming focused on data science and AI workflows. Gained hands-on experience in working with data structures, libraries like NumPy and Pandas, and built small AI-enabled projects using Python.

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Build a Computer Vision App with Azure Cognitive Services – Microsoft

Built a real-world computer vision app using Microsoft Azure’s AI services. Learned how to integrate cloud-based image recognition, face detection, and object classification into applications using minimal code.

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Geospatial Analysis (Pandas) – Kaggle

Learned how to work with geospatial data using Python and Pandas. This course covered geospatial joins, coordinate reference systems, and visualizing location-based data—essential skills for analyzing and mapping real-world patterns.

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Pandas – Kaggle

Mastered data manipulation with Pandas, one of the most powerful Python libraries for data analysis. This course focused on real-world datasets, covering everything from data cleaning to aggregation and visualization.

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Developing LLM Applications with LangChain – DataCamp

Learned how to build applications powered by large language models using LangChain. The course covered prompt engineering, chaining LLM components, memory integration, and building intelligent agents for real use cases.

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Object-Oriented Programming in Java – DataCamp

Gained a solid understanding of object-oriented programming concepts in Java, including classes, inheritance, polymorphism, and encapsulation. Developed small Java-based applications with clean, modular code architecture.