Data Science

This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus.

Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Sci-Kit Learn

Learn the critical elements of Data Science, from visualization to databases to Python and more, in just 6 weeks!

This website contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks.

Learn how to apply probability and statistics to real data science and business applications!

Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2

R Programming for Data Science & Data Analysis. Applying R for Statistics and Data Visualization with GGplot2 in R

Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis

The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers. We'll cover the machine learning and data mining techniques real employers are looking for, including:

• Regression analysis

• K-Means Clustering

• Principal Component Analysis

• Train/Test and cross validation

• Bayesian Methods

• Decision Trees and Random Forests

• Multivariate Regression

• Multi-Level Models

• Support Vector Machines

• Reinforcement Learning

• Collaborative Filtering

• K-Nearest Neighbor

• Bias/Variance Tradeoff

• Ensemble Learning

• Term Frequency / Inverse Document Frequency

• Experimental Design and A/B Tests

Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more!

Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.

Become a SQL query wizard and never be afraid to look at a large SQL query again!

Take Your R & R Studio Skills To The Next Level. Data Analytics, Data Science, Statistical Analysis in Business, GGPlot2

Understand what deep learning is for and how it is used | Decent Python coding skills, especially tools for data science (Numpy, Matplotlib) | Preferable to have experience with RNNs, LSTMs, and GRUs | Preferable to have experience with Keras | Preferable to understand word embeddings

Build artificial neural networks with Tensorflow and Keras | Classify images, data, and sentiments using deep learning | Make predictions using linear regression, polynomial regression, and multivariate regression | Data Visualization with MatPlotLib and Seaborn | Implement machine learning at massive scale with Apache Spark's MLLib | Understand reinforcement learning - and how to build a Pac-Man bot | Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA | Use train/test and K-Fold cross validation to choose and tune your models | Build a movie recommender system using item-based and user-based collaborative filtering | Clean your input data to remove outliers | Design and evaluate A/B tests using T-Tests and P-Values