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  Courses      Module 1     Module 2      Module 3     Module 4     Module 5     Module 6    

📖 Learning Outcomes

After completing Module 2, you will:

1. Data Cleaning and Normalization:

   • Understand and apply techniques to clean and normalize text data.

   • Remove duplicates and handle special characters effectively.

2. Tokenization:

   • Split text into meaningful tokens suitable for embedding generation.

   • Implement various tokenization methods using different libraries.

3. Managing Large Datasets:

   • Handle and process large datasets efficiently using scalable tools like Dask or PySpark.

   • Optimize data processing pipelines for performance and scalability.

4. Integrated Pipeline Development:

   • Develop an end-to-end pre-processing pipeline that integrates cleaning, normalization, tokenization, and efficient data handling.

   • Prepare data for embedding generation and downstream machine learning tasks.