Are you an Artificial Intelligence enthusiast looking to expand your skills and knowledge in the field? If yes, then Deep Learning for Beginners in Python: Work On 12+ Projects course is the perfect fit for you! This course offers an in-depth understanding of Deep Learning and its complexities in an easy and comprehensive manner.
What the Course Offers
Deep Learning for Beginners in Python: Work On 12+ Projects course aids in providing hands-on experience on various projects that include Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transfer Learning, Natural Language Processing (NLP), Data Science, and Data Visualization utilizing the TensorFlow 2.0 Framework with Python programming language.
The course sets a foundation for building your Neural Networks from scratch and acquiring a complete understanding of ANNs, CNNs, and RNNs.
Deep Learning for Beginners in Python: Work On 12+ Projects course helps in:
1. Building Neural Networks with Long Short Term Memory (LSTM) and Gated Recurrent Units (GRU).
2. Gaining knowledge of Transfer learning to cater to the problems of “not enough data” and “training time is very long”.
3. Learning NLP and Text Classification by working on a project on Movie Review Classification with Natural Language Toolkit (NLTK).
4. Enhancing skills in Data Analysis with Numpy and Pandas and Data Visualization with Matplotlib, and more.
Course Rating and Reviews
The course has an excellent aggregate rating of 4.40188 and 146 reviews from satisfied learners who have commended the course for its practical approach and comprehensive understanding of Deep Learning and its applications.
One of the reviews states, “I am glad that I enrolled in this deep learning course. Vijay Gadhave has a great way of presenting the material in a way that is easy to understand but also dives deep enough to give a real understanding of the subject. Good presentation and good examples.”
Projects of the Course
The course has over 12+ projects in various topics such as:
Artificial Neural Networks (ANNs)
The course offers two Artificial neural network projects where you will learn to perform Multiclass Image Classification with ANN and Binary Data Classification with ANN.
Convolutional Neural Networks (CNNs)
The course has five projects associated with Convolutional Neural Networks that involve Object Recognition in Images with CNN, Binary Image Classification with CNN, Digit Recognition with CNN, Breast Cancer Detection with CNN, and Credit Card Fraud Detection with CNN.
Recurrent Neural Networks (RNNs)
The course provides three RNN projects that include IMDB Review Classification with RNN - LSTM, Multiclass Image Classification with RNN - LSTM, and Google Stock Price Prediction with RNN and LSTM.
Transfer Learning
The course covers an essential topic of Transfer Learning that helps with the issues of insufficient data and extended training time, enhancing the learning experience and deepening one’s understanding.
Natural Language Processing (NLP)
Deep Learning for Beginners in Python: Work On 12+ Projects course provides an NLP segment where you get to know the basics of NLP and its relevance. In addition, you get hands-on experiences of Text Classification with NLTK working on a project on Movie Review Classification.
Data Analysis and Data Visualization
The course includes a Data analysis and visualization segment, providing a Crash Course on Numpy (Data Analysis), Crash Course on Pandas (Data Analysis), and a Crash course on Matplotlib (Data Visualization) that helps enhance the skills in Data Analysis with Numpy and Pandas and Data Visualization with Matplotlib.
Course creator
The Course is designed and curated by Vijay Gadhave, a top-rated instructor with a Ph.D. in Computer Science. Vijay Gadhave has over 20 years of experience in providing practical knowledge to learners through various avenues such as online and classroom training, corporate workshops, and academia-based courses. The course is structured with a focus on providing an uncomplicated and comprehensible approach to learning.
Cost and Time frame
The course is available on Udemy and costs $129.99. On completion of the course, Udemy provides a certificate of completion acknowledging the hours spent dedicatedly learning the course. The course content is available for a lifetime, removing any time restriction or lapse in coverage.
Deep Learning for Beginners in Python: Work On 12+ Projects course can be accessed from anywhere and everywhere as long as an individual has stable internet connectivity. The time frame for the course is flexible, allowing learners to complete the course material at their pace and convenience.
Is it Worth it?
Deep Learning for Beginners in Python: Work On 12+ Projects course offers hands-on experience on various projects, catering to the needs of varying audiences, be it an individual looking to brush up on their existing skills or new learners starting to explore the field. The course content is structured to provide comprehensive knowledge, in a practical way, at a flexible time frame and affordable cost. The course rating and feedback of learners signify the quality offered. So, indeed, it is worth giving a try.
Enroll now in Deep Learning for Beginners in Python: Work On 12+ Projects course and gain expertise in the field of Artificial Intelligence and Deep Learning.
