Learn Deep Learning vs TensorFlow Practice Test
Price, ratings, monetisation and update history for both apps, side by side — with what reviewers say about each.
Learn Deep Learning
Master deep learning, neural networks, and AI with a comprehensive curriculum. Learn from Python fundamentals to building and deploying advanced AI models, becoming a job-ready AI engineer.
- Deep Learning Fundamentals
- Core AI Architectures (CNNs, RNNs, Transformers)
- Popular Libraries & Frameworks (PyTorch, TensorFlow)
- Computer Vision & MLOps
- Model Deployment & Cloud Infrastructure
- Edge & Mobile AI
- AI Security & Ethics
Read full descriptionHide full description
Master Deep Learning, Neural Networks, and Artificial Intelligence with the most comprehensive learning app. From Python fundamentals to training Large Language Models (LLMs), building Generative AI apps, and deploying models to the cloud — this is your complete path to becoming an AI Engineer. COMPLETE CURRICULUM - Zero to AI Expert.Start from scratch and become job-ready with our structured learning path: Deep Learning Fundamentals: • Introduction to Deep Learning & Neural Networks • How Deep Learning differs from traditional Machine Learning • Artificial Neural Networks (ANN) architecture & training • Loss Functions, Optimizers (Adam, SGD, RMSprop) • Regularization: Dropout, Batch Norm, L1/L2 Core Architectures: • Convolutional Neural Networks (CNNs) for Computer Vision • Recurrent Neural Networks (RNNs), LSTM & GRU for sequences • Transformers: Attention mechanism • Generative Models: GANs, VAEs, Diffusion Models • Autoencoders & Self-Supervised Learning Libraries & Frameworks: • PyTorch: Tensors, Autograd, nn.Module, training loops • TensorFlow & Keras: Sequential, Functional API, model deployment • JAX: High-performance ML research framework • NumPy, Pandas, Scikit-learn, SciPy foundations Computer Vision: • Image Classification with CNNs • Object Detection: YOLO, R-CNN, SSD • Image Segmentation: U-Net, Mask R-CNN • Face Recognition & Facial Landmarks MLOps & Engineering: • ML lifecycle management & experiment tracking • MLflow, Weights & Biases (W&B) for logging • Kubeflow pipelines & Apache Airflow orchestration • CI/CD for Machine Learning • Model versioning, registries & A/B testing • Monitoring, drift detection & model retraining Production & Deployment: • FastAPI & Flask for serving ML models • gRPC for high-performance model inference • Docker containerization for ML apps • Load balancing, caching & request queuing • PostgreSQL, MongoDB & Redis integration • Vector databases: Pinecone, Weaviate, Milvus for RAG Cloud Infrastructure: • AWS SageMaker, EC2, Lambda for ML workloads • Azure Machine Learning platform • Kubernetes (K8s) & Helm for ML orchestration Hardware & Compute • NVIDIA GPUs, CUDA cores & Tensor cores • Neural Processing Units (NPU) & Apple Neural Engine Edge & Mobile AI: • TensorFlow Lite for mobile deployment • Core ML for iOS apps • ONNX for cross-platform model export AI Security & Ethics: • AI safety & alignment fundamentals • Adversarial attacks & robustness • Data poisoning & model stealing defenses • Fairness, bias detection & mitigation Specialized Domains: • Medical AI: Diagnosis, radiology, drug discovery • Robotics: Perception, control, reinforcement learning • Financial AI: Trading, fraud detection, risk modeling • Bioinformatics: Protein folding, genomics • Cybersecurity: Threat detection, anomaly detection Research & Expert Topics: • Foundation models, scaling laws & emergent abilities • Mixture of Experts (MoE) & Sparse Transformers • World models, neuro-symbolic AI • Meta-learning, continual learning, curriculum learning AI TUTOR - Your 24/7 Learning Assistant: • Ask any Deep Learning or AI question • Get explanations of neural network architectures • Debug model training issues with AI help GAMIFIED LEARNING - Stay Motivated: • Daily learning streaks with fire animations • XP points & level progression • Study reminders with push notifications POWERFUL ORGANIZATION TOOLS: • Bookmarks: Save lessons for quick access • Notes: Write personal notes on any lesson • Search: Find anything instantly across all lessons • Dark mode for comfortable night learning LEARN OFFLINE - Anytime, Anywhere: • All content are offline access • Study on your commute without internet PERFECT FOR: • Aspiring AI & Machine Learning Engineers • Data Scientists expanding into Deep Learning • Software developers transitioning to AI • Students studying computer science or AI • Career changers entering the AI field Start your Deep Learning Journey today !
TensorFlow Practice Test
Read full descriptionHide full description
TensorFlow Developer gives you focused mobile practice built around DeepLearning.AI TensorFlow Developer Professional Certificate. Use the app to: - answer more daily questions - target your weakest domain - review explanations and source-backed answers - track exam readiness over time - move into longer timed practice sessions The website gives you a clean daily sample. The app gives you the fuller study flow, larger rotating bank, and better progress tracking. Terms of Use (EULA): https://www.apple.com/legal/internet-services/itunes/dev/stdeula/ Privacy Policy: https://dotcreds.com/privacy.html
Screenshots
Verdict
The clearest difference is price: TensorFlow Practice Test at Free against Learn Deep Learning's $2.99. TensorFlow Practice Test also leads on update cadence (every 4 weeks vs every 4 months) and iOS requirement (15.1 vs 17). Learn Deep Learning's advantage is in-app purchases (none vs 3). On ads and device support there is nothing between them.
Scored on Price · Rating · Positive reviews · Number of ratings · Update frequency · Ads · In-app purchases · Monetization · Best chart rank · Devices · Requires iOS
TensorFlow Practice Test is free to download; Learn Deep Learning costs $2.99 up front. TensorFlow Practice Test sells 3 in-app purchases, starting at $6.99 per month. Learn Deep Learning asks for nothing beyond the download.
Learn Deep Learning ships an update every 4 months, TensorFlow Practice Test every 4 weeks. The most recent releases landed on October 3, 2026 and October 10, 2026 respectively.
| Parameter | Learn Deep Learning | TensorFlow Practice Test |
|---|---|---|
| Price | $2.99 | Free — better |
| Rating | 5.0 (2 ratings) — better | — |
| Number of ratings | 2 — better | — |
| Update frequency | Every 4 months | Every 4 weeks — better |
| Ads | No | No |
| In-app purchases | No — better | Yes |
| Monetization | Paid | — |
| Devices | iPhone, iPad | iPhone, iPad, iPod — better |
| Requires iOS | 17 | 15.1 — better |
| Further details — not scored | ||
| Size | 188 MB | 40 MB |
| Age rating | 9+ | 4+ |
| Developer | Shahbaz Khan | Thomas Baric |
In-app purchases
Learn Deep Learning
No in-app purchases
TensorFlow Practice Test
- Linux / DevOps Access Bundle$6.991 Month
- AI / Machine Learning Access Bundle$6.991 Month
- TensorFlow Developer Pro$3.99
Questions
Is Learn Deep Learning free?
Is TensorFlow Practice Test free?
Do Learn Deep Learning or TensorFlow Practice Test have ads?
Which is updated more often, Learn Deep Learning or TensorFlow Practice Test?
Other comparisons















