Python Datacamp Skill & Career Tracks

Completed Career Tracks at DataCamp

Python Programmer

  1. Introduction to Python
  2. Intermediate Python
  3. Python Data Science Toolbox (Part 1 & 2)
  4. Introduction to Importing Data in Python
  5. Intermediate Importing Data in Python
  6. Cleaning Data in Python
  7. pandas Foundations
  8. Manipulating DataFrames with pandas
  9. Merging DataFrames with pandas
  10. Introduction to Relational Databases in SQL
  11. Introduction to Shell
  12. Conda Essentials

Data Scientist with Python 

  1. Introduction to Python
  2. Intermediate Python
  3. Python Data Science Toolbox (Part 1 & 2)
  4. Introduction to Importing Data in Python
  5. Intermediate Importing Data in Python
  6. Cleaning Data in Python
  7. pandas Foundations
  8. Manipulating DataFrames with pandas
  9. Merging DataFrames with pandas
  10. Analyzing Police Activity with pandas
  11. Introduction to SQL
  12. Introduction to Relational Databases in SQL
  13. Introduction to Data Visualization in Python
  14. Interactive Data Visualization with Bokeh
  15. Statistical Thinking in Python (Part 1 & 2)
  16. Joining Data in SQL
  17. Introduction to Shell
  18. Conda Essentials
  19. Supervised Learning with scikit-learn
  20. Machine Learning with the Experts: School Budgets
  21. Unsupervised Learning in Python
  22. Machine Learning with Tree-Based Models in Python
  23. Introduction to Deep Learning in Python
  24. Network Analysis in Python (Part 1)

Data Analyst in Python

  1. Introduction to Data Science in Python
  2. Intermediate Python
  3. Python Data Science Toolbox (Part 1)
  4. Introduction to SQL
  5. Joining Data in SQL
  6. Introduction to Relational Databases in SQL
  7. Introduction to Importing Data in Python
  8. Intermediate Importing Data in Python
  9. Cleaning Data in Python
  10. pandas Foundations
  11. Manipulating DataFrames with pandas
  12. Merging DataFrames with pandas
  13. Analyzing Police Activity with pandas
  14. Introduction to Data Visualization in Python
  15. Statistical Thinking in Python (Part 1 &  2)

Machine Learning Scientist with Python

  1. Supervised Learning with scikit-learn
  2. Unsupervised Learning in Python
  3. Linear Classifiers in Python
  4. Machine Learning with Tree-Based Models in Python
  5. Extreme Gradient Boosting with XGBoost
  6. Clustering Methods with SciPy
  7. Dimensionality Reduction in Python
  8. Preprocessing for Machine Learning in Python
  9. Machine Learning for Time Series Data in Python
  10. Feature Engineering for Machine Learning in Python
  11. Model Validation in Python
  12. Introduction to Natural Language Processing in Python
  13. Feature Engineering for NLP in Python
  14. Introduction to TensorFlow in Python
  15. Introduction to Deep Learning in Python
  16. Introduction to Deep Learning with Keras
  17. Advanced Deep Learning with Keras
  18. Image Processing in Python
  19. Image Processing with Keras in Python
  20. Hyperparameter Tuning in Python
  21. Introduction to PySpark
  22. Machine Learning with PySpark
  23. Winning a Kaggle Competition in Python

 

Completed Skill Tracks at DataCamp

Python Programming

  1. Intro to Python
  2. Intermediate Python
  3. Python Data Science Toolbox (Part 1 & 2)

Importing & Cleaning 

  1. Introduction to Importing Data in Python
  2. Intermediate Importing Data in Python
  3. Introduction to Databases in Python
  4. Cleaning Data in Python

Data Manipulation with Python

  1. pandas Foundations
  2. Manipulating DataFrames with pandas
  3. Merging DataFrames with pandas
  4. Analyzing Police Activity with pandas

Machine Learning Fundamentals

  1. Supervised Learning with scikit-learn
  2. Unsupervised Learning in Python
  3. Linear Classifiers in Python
  4. Machine Leaning with Experts : School Budgets
  5. Introduction to Deep Learning in Python

Time Series

  1. Time Series Analysis in Python
  2. Manipulating Time Series Data in Python
  3. Visualizing Time Series Data in Python
  4. Forecasting Using ARIMA Models in Python
  5. Machine Learning for Time Series Data in Python

Statistics Fundamentals

  1. Statistical Thinking in Python (Part 1 & 2)
  2. Introduction to Linear Modeling in Python
  3. Statistical Simulation in Python
  4. Case Studies in Statistical Thinking

Data Visualization

  1. Introduction to Data Visualization with Mathplotlib
  2. Introduction to Data Visualization with Seaborn
  3. Improving your Data Visualization in Python
  4. Interactive Data Visualization with Bokeh
  5. Visualizing Geospatial Data in Python

Image Processing

  1. Image Processing in Python
  2. Biomedical Image Analysis in Python
  3. Image Processing with Keras in Python

Python Toolbox

  1. Dealing with Missing Data in Python
  2. Working with Dates and Times in Python
  3. Regular Expressions in Python
  4. Writing Efficient Python Code
  5. Practicing Coding Interview Questions in Python

Big Data with PySpark

  1. Introduction to PySpark
  2. Big Data Fundamentals with PySpark
  3. Cleaning Data with PySpark
  4. Feature Engineering with PySpark
  5. Machine Learning with PySpark
  6. Building Recommendation Engines with PySpark

Coding Best Practices

  1. Writing Efficient Python Code
  2. Optimizing Python Code with pandas
  3. Writing Functions in Python
  4. Object-Oriented Programming in Python
  5. Creating Robust Python Workflows
  6. Software Engineering for Data Scientists in Python
  7. Unit Testing for Data Science in Python

Marketing Analytics in Python

  1. Predicting Customer Churn in Python
  2. Customer Analytics and A/B Testing in Python
  3. Customer Segmentation in Python
  4. Machine Learning for Marketing in Python