Core NLP with Deep Learning
Master core NLP,Deep Learning with Artificial Neural Networks, TensorFlow, Keras, and real-world projects to build intelligent AI applications.
Created by Balaji Gangadharam
What's Included With This Course
Every course comes bundled with matching study materials, interview question packs, and scenario-based questions — no extra purchase needed.
Study Materials
Cheat sheets, PDF notes, architecture diagrams, and revision cards for this topic.
- ✓ Topic-specific cheat sheets
- ✓ Annotated code examples
- ✓ Quick revision cards
Interview Questions
Curated questions with detailed answers, company tags, and explanations matched to this course.
- ✓ Detailed model answers
- ✓ Company-tagged questions
- ✓ Difficulty-graded sets
Scenario-Based Questions
Real-world system design and production scenario questions to prepare you for interviews.
- ✓ System design scenarios
- ✓ Production debugging cases
- ✓ Architecture trade-off questions
About This Course
Deep Learning is one of the most transformative technologies powering today's Artificial Intelligence revolution. From computer vision and speech recognition to recommendation systems and Generative AI, Deep Learning models are solving complex real-world problems across industries.
This course is designed to help students, developers, and AI enthusiasts build a strong foundation in Deep Learning by combining theoretical concepts with practical implementation. Beginning with Artificial Neural Networks (ANNs), you'll understand how neural networks work, how they learn from data, and how modern deep learning architectures are built.
Throughout the course, you'll gain hands-on experience using TensorFlow and Keras to build, train, evaluate, and optimize deep learning models. Learn essential concepts such as activation functions, loss functions, optimizers, forward propagation, backward propagation, feature scaling, model evaluation, callbacks, and deployment-ready workflows.
The course also includes interview-focused preparation with hundreds of MCQs, interview questions, scenario-based exercises, business use cases, and personalized mentorship to prepare you for roles such as Deep Learning Engineer, AI Engineer, and Data Scientist.
Skills You Will Learn
Prerequisites
- Basic Python knowledge
Projects Included
Customer Churn Prediction using Artificial Neural Networks
intermediateBuild an ANN model to predict customer churn using TensorFlow and Keras. Learn data preprocessing, feature scaling, model training, evaluation, and prediction.
Employee Salary Prediction with Deep Learning
intermediateDevelop a regression model using Artificial Neural Networks to predict employee salaries based on multiple input features while learning optimization and loss functions.
Customer Purchase Prediction
intermediateCreate a Deep Learning classification model that predicts whether a customer is likely to purchase a product using ANN, feature engineering, and evaluation metrics.
End-to-End Deep Learning Business Use Case
advancedImplement a complete Deep Learning pipeline from data preprocessing and feature scaling to ANN model building, training, evaluation, optimization, and prediction using TensorFlow and Keras.
Course Curriculum
Meet Your Instructor
Balaji Gangadharam
Founder, Product Director & Generative AI Architect at Webvoid Technologies
Balaji Gangadharam is a Generative AI Architect, Product Director, and technology leader with extensive experience in Artificial Intelligence, Natural Language Processing, Deep Learning, Large Language Models, Retrieval-Augmented Generation (RAG), and enterprise-scale software development. As the Product Director at Webvoid Technologies, he has led the design and development of AI-powered products, EdTech platforms, enterprise applications, and intelligent automation solutions. His expertise spans the complete AI lifecycle—from data preprocessing and model development to production deployment, observability, monitoring, and system optimization. Over the years, Balaji has mentored aspiring engineers, software developers, and AI professionals, helping them transition into high-demand technology careers. His teaching approach focuses on building strong foundations, practical implementation, real-world projects, and production-grade engineering practices. Through Webvoid Academy, he aims to bridge the gap between academic learning and industry requirements by providing structured, project-driven, and career-focused programs that prepare learners for roles such as Generative AI Engineer, NLP Engineer, Machine Learning Engineer, Deep Learning Engineer, and AI Solutions Architect.
Click to view profile →What Our Students Say
“Excellent course with practical implementation of TensorFlow and Keras. The projects helped me understand Deep Learning concepts clearly.”
Course Stats
Frequently Asked Questions
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Launch Offer – Limited Time
Enroll NowView CurriculumThis course includes
- 12+ hours of content
- Certificate of completion
- Lifetime access
- English
- Mentor support