The #1 Python Data Scientist: Sentiment Analysis & More
Build a positive/negative review classifier in a ten-lesson/79-minute project after Python/NumPy/pandas/ML/TensorFlow foundations, the whole course counts once and is adjacent technical training
Build a positive/negative review classifier in a ten-lesson/79-minute project after Python/NumPy/pandas/ML/TensorFlow foundations. The whole course counts once and is adjacent technical training
Audience and starting point
Selected published requirements: “No OS requirement but the tutorials are recorded on a Mac with Google Colab”. “No experience necessary”. See the provider page for the full requirements and current tool terms
Access and subscriptions
Recorded Udemy course advertised with a public course preview. Exact lesson count may be unknown. Purchase or organization-subscription terms and current availability require checking
An original example for comparing learning plans. Ask whether the course teaches this task, includes practice and offers feedback; the diagram does not describe a provider’s course.
Implement collaborative filtering, matrix factorization, neural models and ranking using NumPy/Keras/TensorFlow/Spark, broad technical recommender course is adjacent to personalization marketing
15 sections • 94 lectures • 12h 49m total lengthCheck current priceEnglish
Build a customer-segmentation clustering project in four lessons/33 minutes after Python data preparation and ML fundamentals, broader data science is adjacent
14 sections • 78 lectures • 11h 13m total lengthCheck current priceEnglish
Practical workflow defines a codebook and gold labels, constructs a feature matrix, trains an elastic-net text classifier, then validates on held-out data using metrics and learning curves, Python/scikit-learn/TensorFlow are listed
Four modules. Coursera estimates two weeks at ten hours per week. Three assignmentsCheck current priceEnglish