Cross Validation Data Wrangling Supervised Learning 
Pickl AI
FEBRUARY 12, 2024
Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. Differentiate between supervised and unsupervised learning algorithms.
Pickl AI
SEPTEMBER 12, 2024
Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities. Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset.
Pickl AI
AUGUST 9, 2024
Data Cleaning and Transformation Techniques for preprocessing data to ensure quality and consistency, including handling missing values, outliers, and data type conversions. Students should learn about data wrangling and the importance of data quality.
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