Model Deployment Courses and Certifications

Board Infinity

Deep Learning: Train Neural Networks and Deploy with Docker

Design and train neural networks in PyTorch, track experiments with TensorBoard and Weights & Biases, then serve and scale models via FastAPI and Docker.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course

Gen AI Dev- Agentic AI Solutions and Tool Integrations

Implement agentic AI solutions by developing autonomous systems, integrating model extension frameworks, building collaborative AI systems, and deploying agents in production.

• Coursera
• 2 hours
• Self-Paced
• Paid Course

Career Certificate

Microsoft Generative AI Operations (GenAIOps)

Treat generative AI as an operational discipline: design GenAIOps operating models, optimize RAG pipelines, build CI/CD and observability, and govern costs and content safety.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 5 courses

EDUCBA

Image Captioning with TensorFlow & Streamlit

Build an image captioning system: preprocess image and text data, train CNN-RNN models with TensorFlow, evaluate with BLEU, and deploy a Streamlit app on AWS EC2.

• Coursera
• 2 weeks, 3 hours a week
• Self-Paced
• Paid Course

EDUCBA

Mask Detector with Python & TensorFlow: Build & Deploy

Build a COVID-19 mask detector: handle images in OpenCV, detect faces with Haar Cascades, train MobileNetV2 in TensorFlow, and deploy the app on AWS.

• Coursera
• 2 weeks, 3 hours a week
• Self-Paced
• Paid Course

Practical Machine Learning without Coding

Build, tune, and deploy machine learning models on no-code platforms: batch training jobs, hyperparameter tuning, bias auditing, error analytics, and API integrations.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

Packt

Data Science Model Deployments and Cloud Computing on GCP

Deploy machine learning models on Google Cloud: containerize apps with Docker and Cloud Run, serve models via App Engine and Cloud Functions, and orchestrate pipelines in Vertex AI.

• Coursera
• 10 weeks, 1 hour a week
• Self-Paced
• Paid Course

Edureka Career Certificate

Transfer Learning and Fine-Tuning for AI Models

Customize pretrained models with transfer learning: apply supervised and instruction fine-tuning with LoRA in PyTorch and Hugging Face, audit fairness, and deploy monitored inference via FastAPI and Docker.

• Coursera
• 92 weeks, 5 hours a week
• Self-Paced
• Paid Course
• 3 courses

Coursera

Optimize and Deploy Edge AI Models

Evaluate model behavior across data slices and apply TensorFlow Lite quantization to weigh size, inference speed, and accuracy trade-offs before deploying to edge devices.

• Coursera
• 1 hour 27 minutes
• Self-Paced
• Paid Course

Edureka

Building and Scaling ML Pipelines

Build production ML pipelines: manage features with Feast, orchestrate distributed training on Kubernetes and Kubeflow Pipelines, and serve models via BentoML, KServe, canary releases and autoscaling.

• Coursera
• 4 weeks, 2 hours a week
• Self-Paced
• Paid Course

Coursera

Build & Optimize TensorFlow ML Workflows

Build an end-to-end TensorFlow 2.x pipeline with tf.data, Keras and custom training loops, then optimize models via TensorFlow Lite post-training quantization and latency benchmarking for edge deployment.

• Coursera
• 2 hours 19 minutes
• Self-Paced
• Paid Course

Packt

Advanced DeepSeek: Fine-Tuning, Optimization, and Deployment

Fine-tune DeepSeek and Gemma 3 for legal reasoning with distillation and LLMOps workflows, then deploy models using quantization, hardware selection, monitoring, and cost management.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

Board Infinity

Fine-Tune Your Own LLM: LoRA, QLoRA & PEFT

Fine-tune open-source LLMs on consumer GPUs with LoRA, QLoRA, and PEFT, prepare chat datasets, apply DPO or ORPO, and deploy with vLLM or Hugging Face Inference Endpoints.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Packt

NVIDIA GenAI & LLMs: Learn and Pass NCA-GENL Certification

Learn to build and customize generative AI systems, understand transformer architecture, select and train models, use NVIDIA CUDA, RAPIDS, TensorRT, and Triton, and prepare for NCA-GENL certification.

• Coursera
• 14 weeks, 1 hour a week
• Self-Paced
• Paid Course

Career Certificate

Microsoft Deep Learning Engineering with Azure

Engineer the full deep learning lifecycle on Azure: implement CNNs, RNNs, and Transformers; fine-tune models with LoRA and QLoRA; scale training with DeepSpeed ZeRO; deploy containerized models.

• Coursera
• Self-Paced
• Paid Course
• 3 courses