Learn Artificial Neural Networks (ANN) in Python. Build predictive deep learning models using Keras & Tensorflow| Python
InstructorStart-Tech AcademyComidoc has tracked 1 coupon for this course since 2025, last checked 1 year, 29 days ago.
| Coupon code | Discount | Added | Status | Lifetime |
|---|---|---|---|---|
| SMARTLEARNFREE | 100% off | Expired | ~4 daysRan full term |
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This slide introduces the course instructors, Abhishek Bansal and Pukhraj Parikh, detailing their educational backgrounds from IIT Roorkee and professional experience in analytics.
This course content overview slide outlines the initial curriculum structure, highlighting key introductory modules such as setting up Python and a comprehensive crash course for beginners.
This course features no prerequisites for beginners and includes practical exercises to reinforce learning through hands-on application.
Instruction follows a logical path from single cells like Perceptrons to stacking cells and complex architectures using the Keras Functional API.
The instructors provide clear, slow-paced explanations of building blocks and hyperparameter considerations to aid understanding.
The curriculum includes specialized add-ons for data preprocessing and classic machine learning models like Linear Regression.
Some learners have noted that programs are presented as code fragments without full library imports, which can complicate following the logic. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.
One signal suggests that specific Python versions used in the course may no longer be readily available, potentially impacting environment setup. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
The curriculum aligns well with the stated goals of beginners and data science students through its foundational approach.