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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Supervised Machine Learning | 15% | - Classification and regression algorithms - Feature engineering and selection - Model training, validation and evaluation |
| Topic 2: Data Acquisition, Preparation and Exploration | 15% | - Data collection methods (SQL, web scraping, APIs) - Data cleaning, transformation and normalization - Exploratory data analysis and visualization |
| Topic 3: Machine Learning for Cybersecurity | 15% | - Malware analysis and classification - Security monitoring and anomaly detection - Threat hunting and behavioral analytics |
| Topic 4: Deep Learning and Neural Networks | 13% | - Convolutional Neural Networks (CNN) - Neural network fundamentals - Autoencoders and generative models |
| Topic 5: Statistics and Probability for Data Science | 15% | - Statistical testing and hypothesis testing - Probability theory and distributions - Descriptive and inferential statistics |
| Topic 6: Unsupervised Machine Learning | 12% | - Anomaly detection techniques - Pattern recognition in security data - Clustering and dimensionality reduction |
| Topic 7: Python for Machine Learning | 15% | - Machine learning frameworks (Scikit-learn, TensorFlow, PyTorch) - Scripting and automation for security data - Data science libraries (Pandas, NumPy, Matplotlib) |
What is the Fourier Series used for in data science?
Response:
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What is the main purpose of the 'softmax' function in neural networks?
Response:
Correct Answer: D 🗳️
What is the t-test a statistical method used for in machine learning?
Response:
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Which of the following are advantages of using Support Vector Machines (SVM) for classification tasks?
(Choose two )
Response:
Correct Answer: B,C 🗳️
You are tasked with building a classification model to predict whether customers will purchase a product based on their browsing behavior. You decide to use a Random Forest classifier. After training the model, you notice that the training accuracy is very high, but the validation accuracy is much lower.
What might be causing this, and how can you improve the model's generalization?
Response:
Correct Answer: A 🗳️
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