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Data Science

Beginner
  • Python for Data Analysis: Pandas, NumPy, and basic data manipulation.

  • Introduction to Data Visualization: Matplotlib and Seaborn.

  • Fundamentals of Machine Learning: Algorithms, evaluation metrics, and basic models.

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Intermediate
  • Feature Engineering and Data Cleaning: Techniques for improving model performance.

  • Building ML Models with TensorFlow and PyTorch: Implementing and training models.

  • EDA and Statistical Methods: In-depth analysis using statistics and visualization.

Advanced
  • Advanced NLP with Transformers: BERT, GPT, and Hugging Face.

  • Big Data Analysis with Spark: Data pipelines and distributed computing.

  • Deploying ML Models (MLOps): Model serving, monitoring, and scaling.

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DevOps

Master the tools and practices to streamline software development and operations

JavaScript

Build dynamic, responsive web experiences with the power of JavaScript

Data Science

Dive into the world of data to uncover insights and drive smarter decisions

GenAI

Unleash creativity with AI that generates text, images, and innovative solutions 

IOT

Transform devices into smart solutions with cutting-edge IoT technologies

Power Platform

Empower your business with no-code tools for apps, automation, and analytics

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