Data Science & Machine Learning

0/27 concepts·~11 h left

Phase 010/4 · ~1.5 h left

Step 1: Learn the Basics of Data Science

Introduction to Data Science25 min

Statistics and Probability25 min

Data Manipulation and Cleaning25 min

Data Visualization25 min

Phase 020/4 · ~1.5 h left

Step 2: Understand Machine Learning Fundamentals

Supervised Learning25 min

Unsupervised Learning25 min

Model Evaluation and Validation25 min

Feature Engineering25 min

Phase 030/9 · ~4 h left

Step 3: Learn Machine Learning Algorithms

Linear Regression25 min

Logistic Regression25 min

Decision Trees and Random Forests25 min

Support Vector Machines25 min

Naive Bayes25 min

K-Nearest Neighbors25 min

Clustering Algorithms25 min

Dimensionality Reduction25 min

Ensemble Methods25 min

Phase 040/5 · ~2 h left

Step 4: Gain Practical Experience

Working with Real-world Datasets25 min

Implementing Machine Learning Models25 min

Model Evaluation and Hyperparameter Tuning25 min

Handling Imbalanced Data25 min

Dealing with Missing Data25 min

Phase 050/5 · ~2 h left

Step 5: Deep Dive into Advanced Topics

Deep Learning and Neural Networks25 min

Natural Language Processing25 min

Reinforcement Learning25 min

Time Series Analysis25 min

Recommendation Systems25 min