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What are the Best Data Science Courses on Udemy?
Below you’ll find the most highly rated and recommended data science courses on Udemy
The Data Science Course 2021: Complete Data Science Bootcamp
What you’ll learn
- The course provides the entire toolbox you need to become a data scientist
- Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
- Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
Statistics for Data Science and Business Analysis
What you’ll learn
- Understand the fundamentals of statistics
- How to plot different types of data
- Make data driven decisions
- Understand the concepts needed for data science even with Python and R!
- Calculate the measures of central tendency, asymmetry, and variability
- Use and understand dummy variables
- Distinguish and work with different types of distributions
R Programming A-Z™: R For Data Science With Real Exercises!
What you’ll learn
- Learn to program in R at a good level
- Learn how to create a while() loop and a for() loop in R
- Learn how to create variables
- Understand the Normal distribution
- Practice working with financial data in R
Machine Learning, Data Science and Deep Learning with Python
What you’ll learn
- Build artificial neural networks with Tensorflow and Keras
- Make predictions using linear regression, polynomial regression, and multivariate regression
- Implement machine learning at massive scale with Apache Spark’s MLLib
- Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
- Build a movie recommender system using item-based and user-based collaborative filtering
- Design and evaluate A/B tests using T-Tests and P-Values
- Classify images, data, and sentiments using deep learning
- Understand reinforcement learning – and how to build a Pac-Man bot
- Use train/test and K-Fold cross validation to choose and tune your models
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