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The text provides a 3-month plan for learning data science with topics including data analysis, Python, statistics, visualization, machine learning, deep learning, databases, Hadoop, MapReduce, Spark, and big data. Recommended resources are provided with a Kaggle project at the end of each month.

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Learn DataScience

The text provides a 3-month plan for learning data science with topics including data analysis, Python, statistics, visualization, machine learning, deep learning, databases, Hadoop, MapReduce, Spark, and big data. Recommended resources are provided with a Kaggle project at the end of each month.

Learn Data Science in 3 Months

Accelerated Learning Techniques

  • Watch videos at 2x or 3x speed using a browser extension
  • Handwrite notes as you watch for memory retention
  • Immerse yourself in the community

Month 1 - Data Analysis

Week 1 - Learn Python

Week 2 - Statistics & Probability

Week 3 Data Pre-processing, Data Visualization, Exploratory Data Analysis

Week 4 Kaggle Project #1

  • Try your best at a competition of your choice from Kaggle.
  • Use Kaggle Learn as a helpful guide

Month 2 - Machine Learning

Math of Machine Learning Cheat Sheets

Week 1-2 - Algorithms & Machine Learning

Week 3 - Deep Learning

Week 4 - Kaggle Project #2

  • Try your best at a competition of your choice from Kaggle. Make sure to add great documentation to your github repository! Github is the new resume.

Month 3 - Real-World Tools

Week 1 Databases (SQL + NoSQL)

Week 2 Hadoop & Map Reduce + Spark

Week 3 Big Data

Week 4 Kaggle Project #3

  • Try your best at a competition of your choice from Kaggle.

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The text provides a 3-month plan for learning data science with topics including data analysis, Python, statistics, visualization, machine learning, deep learning, databases, Hadoop, MapReduce, Spark, and big data. Recommended resources are provided with a Kaggle project at the end of each month.

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