About Course

This course is designed for individuals with a basic understanding of Data Science who want to advance their skills in data analysis, machine learning, and big data processing. You’ll learn advanced data wrangling techniques, predictive modeling, deep learning, and deployment strategies for real-world applications. By the end of this course, you will be able to handle complex data science projects and optimize machine learning models.

What Will You Learn?

  • Advanced data preprocessing techniques (handling missing data, feature engineering)
  • Statistical modeling and hypothesis testing
  • Machine learning model selection and hyperparameter tuning
  • Deep learning fundamentals (Neural Networks, CNNs, RNNs)
  • Natural Language Processing (NLP) techniques for text analysis
  • Time series forecasting and predictive analytics
  • Working with big data technologies (Hadoop, Spark, Dask)
  • Data pipelines and automation with Python (Airflow, Prefect)
  • Model deployment strategies (Flask, FastAPI, Docker)
  • Ethics, fairness, and bias in data science models

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