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DataCamp: 1) Data Scientist with Python 2) Data Analyst with Python 3) Data Analyst with SQL Server 4) Machine Learning Scientist with Python

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DataCamp

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Contents

Career Tracks

  1. Data Scientist with Python
  2. Data Analyst with Python
  3. Data Analyst with SQL Server
  4. Data Science for Everyone
  5. Machine Learning Scientist with Python

Skill Tracks

Data Scientist with Python

Course Slides Dataset Notes Solutions
Introduction to Python - - - -
Intermediate Python - - - -
PROJECT TV, Halftime Shows, and the Big Game - - - -
Data Manipulation with pandas - - - -
PROJECT The Android App Market on Google Play - - - -
Merging DataFrames with pandas - - - -
PROJECT The GitHub History of the Scala Language - - - -
Introduction to Data Visualization with Matplotlib - - - -
Introduction to Data Visualization with Seaborn - - - -
Python Data Science Toolbox (Part 1) - - link -
Python Data Science Toolbox (Part 2) - - - -
Intermediate Data Visualization with Seaborn - - - -
PROJECT A Visual History of Nobel Prize Winners - - - -
Introduction to Importing Data in Python - - - -
Intermediate Importing Data in Python - - - -
Importing & Cleaning Data with Python - - - -
Cleaning Data in Python - - - -
Working with Dates and Times in Python - - - -
Writing Functions in Python - - - -
Exploratory Data Analysis in Python - - - -
Analyzing Police Activity with pandas - - - -
Statistical Thinking in Python (Part 1) - - - -
Statistical Thinking in Python (Part 2) - - - -
PROJECT Dr. Semmelweis and the Discovery of Handwashing - - - -
Supervised Learning with scikit-learn - - - -
PROJECT Predicting Credit Card Approvals - - - -
Unsupervised Learning in Python - - - -
Machine Learning with Tree-Based Models in Python - - - -
Case Study: School Budgeting with Machine Learning in Python - - - -
Cluster Analysis in Python - - - -

Data Analyst with Python

Course Slides Dataset Notes Solutions
Introduction to Data Science in Python - - - -
Intermediate Python - - - -
Data Manipulation with pandas - - - -
Merging DataFrames with pandas - - - -
Introduction to Data Visualization with Matplotlib - - - -
Introduction to Data Visualization with Seaborn - - - -
Introduction to Importing Data in Python - - - -
Intermediate Importing Data in Python - - - -
Cleaning Data in Python - - - -
Exploratory Data Analysis in Python - - - -
Analyzing Police Activity with pandas - - - -
Introduction to SQL - - - -
Streamlined Data Ingestion with pandas - - - -
Introduction to Relational Databases in SQL - - - -
Joining Data in SQL - - - -
Introduction to Databases in Python - - - -

Data Analyst with SQL Server

Course Solutions
Introduction to SQL Server link
Introduction to Relational Databases in SQL link
Intermediate SQL Server link
Time Series Analysis in SQL Server -
Functions for Manipulating Data in SQL Server -
Database Design link
Hierarchical and Recursive Queries in SQL Server -
Transactions and Error Handling in SQL Server -
Writing Functions and Stored Procedures in SQL Server -
Building and Optimizing Triggers in SQL Server link
Improving Query Performance in SQL Server -

Data Science for Everyone

Course Slides Dataset Notes Solutions
Introduction to Python - - - -
Intermediate Python - - - -
Python Data Science Toolbox (Part 1) - - - -
Python Data Science Toolbox (Part 2) - - - -
Introduction to Importing Data in Python - - - -
Intermediate Importing Data in Python - - - -
Cleaning Data in Python - - - -
Data Manipulation with pandas - - - -
Merging DataFrames with pandas - - - -
Analyzing Police Activity with pandas - - - -
Introduction to SQL - - - -
Introduction to Relational Databases in SQL - - - -
Introduction to Data Visualization with Matplotlib - - - -
Introduction to Data Visualization with Seaborn - - - -
Statistical Thinking in Python (Part 1) - - - -
Statistical Thinking in Python (Part 2) - - - -
Joining Data in SQL - - - -
Introduction to Shell - - - -
Conda Essentials - - - -
Supervised Learning with scikit-learn - - - -
Case Study: School Budgeting with Machine Learning in Python - - - -
Unsupervised Learning in Python - - - -
Machine Learning with Tree-Based Models in Python - - - -
Introduction to Deep Learning in Python - - - -
Introduction to Network Analysis in Python - - - -

Machine Learning Scientist with Python

Course Slides Dataset Notes Solutions
Machine Learning for Everyone - - - -
Introduction to Python - - - -
Intermediate Python - - - -
Python Data Science Toolbox (Part 1) - - - -
Python Data Science Toolbox (Part 2) - - - -
Statistical Thinking in Python (Part 1) - - - -
Supervised Learning with scikit-learn - - - -
Unsupervised Learning in Python - - - -
Linear Classifiers in Python - - - -
Machine Learning with Tree-Based Models in Python - - - -
Extreme Gradient Boosting with XGBoost - - - -
Cluster Analysis in Python - - - -
Dimensionality Reduction in Python - - - -
Preprocessing for Machine Learning in Python - - - -
Machine Learning for Time Series Data in Python - - - -
Feature Engineering for Machine Learning in Python - - - -
Model Validation in Python - - - -
Introduction to Natural Language Processing in Python - - - -
Feature Engineering for NLP in Python - - - -
Introduction to TensorFlow in Python - - - -
Introduction to Deep Learning in Python - - - -
Introduction to Deep Learning with Keras - - - -
Advanced Deep Learning with Keras - - - -
Image Processing in Python - - - -
Image Processing with Keras in Python - - - -
Hyperparameter Tuning in Python - - - -
Introduction to PySpark - - - -
Machine Learning with PySpark - - - -
Winning a Kaggle Competition in Python - - - -