Data Science
A free learning path covering core machine learning algorithms, with hands-on examples in Python and R, plus an introduction to neural networks.
Learn from: the original creator. Original content published on YouTube. DigitalSkillX organizes these public resources into a structured learning path. DigitalSkillX does not claim ownership or partnership.
Now playing: Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn
This path guides you through the main machine learning algorithms, starting with the fundamentals and moving to practical implementations. You will learn linear and logistic regression, decision trees, random forests, Naive Bayes, support vector machines, K-nearest neighbors, and clustering. The later lessons introduce neural networks, including CNNs and RNNs, and show real-world applications. The material comes from a curated YouTube playlist by Simplilearn, so you can follow along at your own pace.
Beginners who want a structured free introduction before deeper practice.
Lesson 1: Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn
This short video explains the three main types of machine learning: supervised, unsupervised, and reinforcement learning. It gives a quick overview of how each type works and when to use them.
Open on YouTubeLesson 2: Regression Analysis | What Is Regression Analysis | Introduction to Regression Analysis |Simplilearn
This lesson introduces regression analysis, a key technique for predicting continuous outcomes. It uses an Olympic 2022 dataset to show how regression works with the SVM algorithm.
Open on YouTubeLesson 3: Linear Regression Analysis | Linear Regression in Python | Machine Learning Algorithms | Simplilearn
This tutorial covers linear regression in Python, explaining the concept and showing how to implement it. It includes practical examples to help you understand how to build and interpret a linear regression model.
Open on YouTubeLesson 4: Logistic Regression | Logistic Regression in Python | Machine Learning Algorithms | Simplilearn
This video explains logistic regression, a method for binary classification. You will learn how to implement logistic regression in Python and how to evaluate its performance.
Open on YouTubeLesson 5: Decision Tree In Machine Learning | Decision Tree Algorithm In Python |Machine Learning |Simplilearn
This lesson covers decision trees, a popular algorithm for both classification and regression. It shows how to build a decision tree in Python and explains how the algorithm splits data.
Open on YouTubeLesson 6: Random Forest Algorithm - Random Forest Explained | Random Forest in Machine Learning | Simplilearn
This tutorial explains the random forest algorithm, an ensemble method that combines multiple decision trees. You will see how it improves accuracy and how to implement it in Python.
Open on YouTubeLesson 7: Naive Bayes Classifier | Naive Bayes Algorithm | Naive Bayes Classifier With Example | Simplilearn
This video introduces the Naive Bayes classifier, a probabilistic algorithm based on Bayes' theorem. It includes an example to show how the algorithm works and how to apply it.
Open on YouTubeLesson 8: Support Vector Machine - How Support Vector Machine Works | SVM In Machine Learning | Simplilearn
This lesson explains support vector machines (SVM), a powerful algorithm for classification and regression. You will learn how SVM finds the optimal hyperplane to separate classes.
Open on YouTubeLesson 9: KNN Algorithm In Machine Learning | KNN Algorithm Using Python | K Nearest Neighbor | Simplilearn
This tutorial covers the K-nearest neighbors (KNN) algorithm, a simple yet effective method for classification and regression. You will see how to implement KNN in Python and how to choose the value of K.
Open on YouTubeLesson 10: Linear Regression in R | Linear Regression in R With Example | Data Science Algorithms | Simplilearn
This video demonstrates linear regression in R, using a practical example. You will learn how to build a linear regression model in R and interpret the output.
Open on YouTubeLesson 11: Logistic Regression in R | Logistic Regression in R Example | Data Science Algorithms | Simplilearn
This lesson shows how to perform logistic regression in R. It includes an example to illustrate the steps and how to interpret the results.
Open on YouTubeLesson 12: Decision Tree In R | Decision Tree Algorithm | Data Science Tutorial | Machine Learning |Simplilearn
This tutorial covers decision trees in R. You will learn how to build a decision tree model and use it for prediction.
Open on YouTubeLesson 13: Random Forest In R | Random Forest Algorithm | Random Forest Tutorial |Machine Learning |Simplilearn
This video explains how to implement the random forest algorithm in R. It shows the steps to create a random forest model and assess its performance.
Open on YouTubeLesson 14: Support Vector Machine in R | SVM Algorithm Explained with Example | Data Science in R | Simplilearn
This lesson demonstrates support vector machines in R. It includes an example to show how to train an SVM model and make predictions.
Open on YouTubeLesson 15: Hierarchical Clustering | Hierarchical Clustering in R |Agglomerative Clustering |Simplilearn
This tutorial covers hierarchical clustering, an unsupervised learning technique. You will learn about agglomerative clustering and how to perform it in R.
Open on YouTubeLesson 16: What is Neural Network in Machine Learning | Neural Network Explained | Neural Network | Simplilearn
This video provides a comprehensive introduction to neural networks. It explains the structure of a neural network, how it learns, and its applications in machine learning.
Open on YouTubeLesson 17: Neural Network Architectures | Types of Neural Network Architectures | Neural Network | Simplilearn
This lesson covers different types of neural network architectures, including feedforward, convolutional, and recurrent networks. You will learn the differences and use cases for each.
Open on YouTubeLesson 18: Convolutional Neural Network Tutorial (CNN) | How CNN Works | Deep Learning Tutorial | Simplilearn
This tutorial explains convolutional neural networks (CNNs), which are widely used for image recognition. You will learn how CNNs work, including convolution and pooling layers.
Open on YouTubeLesson 19: Recurrent Neural Network (RNN) Tutorial | RNN LSTM Tutorial | Deep Learning Tutorial | Simplilearn
This video covers recurrent neural networks (RNNs) and LSTM networks, which are used for sequence data. You will learn how RNNs handle time series and text data.
Open on YouTubeLesson 20: Machine Learning Full Course | Learn Machine Learning | Machine Learning Tutorial | Simplilearn
This is a full machine learning course video that covers many topics from the playlist. It serves as a comprehensive review and includes practical examples.
Open on YouTubeLesson 21: Machine Learning Algorithms Full Course | Machine Learning Algorithms Explained | Simplilearn
This full course video explains various machine learning algorithms in detail. It is a long-form tutorial that can help solidify your understanding.
Open on YouTubeLesson 22: Machine Learning Full Course 2026 | Complete Machine Learning Training in 24 Hours | Simplilearn
This is a 24-hour machine learning full course video. It provides an extensive training experience, covering many topics from basics to advanced.
Open on YouTubeLesson 23: Python Machine Learning Projects For Beginners 2026 | Machine Learning With Python | Simplilearn
This video presents Python machine learning projects for beginners. It walks through several projects to help you apply what you have learned.
Open on YouTubeLesson 24: Coronavirus Outbreak Prediction Using Machine Learning | Predicted vs Actual | Simplilearn
This lesson shows a real-world application of machine learning: predicting the coronavirus outbreak. It compares predicted vs actual data to illustrate the process.
Open on YouTubeLesson 25: 🔥Free Machine Learning Algorithms Course with Certificate | Machine Learning | Skillup | Simplilearn
This short video introduces a free machine learning algorithms course with a certificate. It is a promotional video but points to additional resources.
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