Complete Data Science Training: Math, Statistics, Python, Advanced Statistics in Python, Machine and Deep Learning
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FreeThe curriculum builds from basic descriptive statistics through to more complex statistical applications.
Instruction includes various quizzes and practical examples to reinforce syntax and statistical concepts.
Editorial course preview
This view highlights a concrete, legible example from the course presentation.
The instructor highlights the course's supplementary resources, specifically pointing out bonus materials such as animations, quizzes, and exercises to support student learning.
The transition from statistics to machine learning can feel abrupt, lacking the mathematical depth found in earlier sections.
The inclusion of TensorFlow 1 and reports of errors with modern scikit-learn syntax suggest the content may not align with current library versions. Note that some negative signals regarding technical friction predated the displayed update, and while the update label may have addressed these issues, it does not prove a correction.
Some learners report a lack of depth in code explanations and an impersonal, potentially automated-feeling delivery style.
The course aligns well with beginners, though the mathematical requirements may be challenging for some learners. Some negative signals regarding technical friction predated the displayed update; while the update label may have addressed these issues, it does not prove a correction.