Specializations (11)

Introduction to Machine Learning in ProductionWhen: Jun, 2021
When: May 2021
Grade Achieved: 90%
Topics: Human Level Performance (HLP), Concept Drift, Model Baseline, Project
Scoping and Design, ML Deployment Challenges

Machine Learning Data Lifecycle in Production
When: May, 2021
Grade Achieved: 95%
Topics: ML Metadata, CNN, TFX, Data Validation and Transformation.

Machine Learning Modeling Pipelines in Production
When: Jul, 2021
Grade Achieved: 100%
Topics: Explainable AI, Fairness Indicators, AutoML, Model Performance Analysis,
Precomputing Predictions etc

Deploying Machine Learning Models in Production
When: Oct, 2021
Grade Achieved: 99%
Topics: TF Serving, Model Monitoring, Model Registries, MLOps, Generate Data
Protection Regulation (GDPR)

Analyze Datasets and Train ML Models using AutoML
When: Jun, 2021
Grade Achieved: 97.50%
Topics: Limits, Prepare Data, Detect Statistical Biases, Perform Feature
Engineering at Scale, Train Models with Pre-Built Algorithms

Build, Train, and Deploy ML Pipelines using BERT
When: Jun, 2021
Grade Achieved: 97%
Topics: ML Pipelines, MLOps, BERT Training, Debugging and Evaluation, Feature
Engineering Artifact and Lineage Tracking

Optimize ML Models and Deploy Human-in-the-Loop Pipelines
When: Aug, 2021
Grade Achieved: 97.90%
Topics: Human in the Loop Pipelines, Distributed Model Training and Hyper-Parameter
Search, A/B Testing, Data Labeling at Scale etc

Math 4 ML: Linear Algebra
Grade Achieved: 98%
Topics: Vector Algebra, Matrices, Determinancts, Linear Mappings, Basis Vectors,
Transformations, Image Manipulation, Gaussian Elimination

Math 4 ML: Multivariate Calculus
Grade Achieved: 97.25%
Topics: Limits, Partial Derivative, Jacobian, Hessian, Multi-Variate Chain Rule,
Neural Networks, Taylor Series etc

Math 4 ML: Principal Component Analysis
Grade Achieved: 96%
Topics: Covariance, Dot Product, Inner Product, nD Subspaces, PCA etc

Getting Started with TF2
Grade Achieved: 94%
Topics: Sequential models, Validation, Regularisation, Callbacks etc

Customising your models with TensorFlow 2
Grade Achieved: 99.88%
Topics: Keras Functional APIs, Data Pipeline, Sequence Modelling, Model
Subclassing and Custom Training Loops

Probabilistic Deep Learning with TensorFlow 2
Grade Achieved: 100%
Topics: Probabilistic Layers, Bayesian Neural Networks, TF-Probability,
Bijectors, Normalising Flows, VAEs etc

Custom Models, Layers, and Loss Functions with TensorFlow
Grade Achieved: 98.75%
Topics: To be updated

Custom and Distributed Training with TensorFlow
Grade Achieved: 96.14%
Topics: To be updated

Advanced Computer Vision with TensorFlow
Grade Achieved: 99.88%
Topics: To be updated

Generative Deep Learning with TensorFlow
Grade Achieved: 100.00%
Topics: To be updated

Build Basic Generative Adversarial Networks
Grade Achieved: 100.00%
Topics: To be updated

Build Better Generative Adversarial Networks
Grade Achieved: 100.00%
Topics: To be updated

Apply Generative Adversarial Networks
Grade Achieved: 93.00%
Topics: To be updated

Natural Language Processing with Classification and Vector Spaces
Grade Achieved: 100.00%
Topics: To be updated

Natural Language Processing with Probabilistic Models
Grade Achieved: 92.73%
Topics: To be updated

Natural Language Processing with Sequence Models
Grade Achieved: 100.00%
Topics: To be updated

Natural Language Processing with Attention Models
Grade Achieved: 97.50%
Topics: To be updated

AI for Medical Diagnosis
Grade Achieved: 83.33%
Topics: To be updated

AI for Medical Prognosis
Grade Achieved: 95.83%
Topics: To be updated

AI For Medical Treatment
Grade Achieved: 100.00%
Topics: To be updated

Browser-based Models with TensorFlow.js
Grade Achieved: 97.59%
Topics: To be updated

Device-based Models with TensorFlow Lite
Grade Achieved: 100.00%
Topics: To be updated

Data Pipelines with TensorFlow Data Services
Grade Achieved: 100.00%
Topics: To be updated

Advanced Deployment Scenarios with TensorFlow
Grade Achieved: 100.00%
Topics: To be updated

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Grade Achieved: 99.29%
Topics: To be updated

Convolutional Neural Networks in TensorFlow
Grade Achieved: 100.00%
Topics: To be updated

Natural Language Processing in TensorFlow
Grade Achieved: 96.88%
Topics: To be updated

Sequences, Time Series and Prediction
Grade Achieved: 100.00%
Topics: To be updated

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Grade Achieved: 100.00%
Topics: To be updated

Sequence Models
Grade Achieved: 99.50%
Topics: To be updated

Convolutional Neural Networks
Grade Achieved: 97.25%
Topics: To be updated

Structuring Machine Learning Projects
Grade Achieved: 93.33%
Topics: To be updated

Neural Networks and Deep Learning
Grade Achieved: 100.00%
Topics: To be updated