SkillAI · The Beam
Machine Learning Engineering
1/41 concepts·~17 h left
1
Phase 010/5 · ~2 h left
Step 1: Understand the Basics of Machine Learning
Supervised Learning25 min
Unsupervised Learning25 min
Reinforcement Learning25 min
Feature Engineering25 min
Model Evaluation25 min
2
Phase 021/5 · ~1.5 h left
Step 2: Learn Programming and Data Manipulation
✓Python Programming25 min
NumPy25 min
Pandas25 min
Data Cleaning25 min
Data Preprocessing25 min
3
Phase 030/9 · ~4 h left
Step 3: Dive into Machine Learning Algorithms
Linear Regression25 min
Logistic Regression25 min
Decision Trees25 min
Random Forests25 min
Support Vector Machines25 min
K-Nearest Neighbors25 min
Naive Bayes25 min
Neural Networks25 min
Gradient Boosting25 min
4
Phase 040/5 · ~2 h left
Step 4: Understand Model Evaluation and Validation
Train-Test Split25 min
Cross-Validation25 min
Evaluation Metrics (Accuracy, Precision, Recall, F1 Score)25 min
Overfitting and Underfitting25 min
Hyperparameter Tuning25 min
5
Phase 050/7 · ~3 h left
Step 5: Explore Advanced Topics in Machine Learning
Dimensionality Reduction25 min
Ensemble Learning25 min
Deep Learning25 min
Natural Language Processing25 min
Recommender Systems25 min
Time Series Analysis25 min
Transfer Learning25 min
6
Phase 060/5 · ~2 h left
Step 6: Gain Practical Experience with Real-World Projects
Data Collection and Preparation25 min
Feature Selection25 min
Model Training and Evaluation25 min
Deployment and Monitoring25 min
Iterative Improvement25 min
7
Phase 070/5 · ~2 h left
Step 7: Stay Updated and Continuously Learn
Reading Research Papers25 min
Participating in Kaggle Competitions25 min
Following Machine Learning Blogs and Forums25 min
Attending Conferences and Workshops25 min
Experimenting with New Techniques and Algorithms25 min
