Certifications

This repositiry is dedicated to different online courses I did on AI, Data Science, Machine Learning, Deep Learning etc.
Click on the name to verify the certificate. Certificates not available as links are either in progress, in approval phase, or to be enrolled in future.

• Machine Learning
• Deep Learning Specialization
  1. Neural Networks and Deep Learning
  2. Improving Deep Neural Networks: Hyperparameter tunning, Regularization and Optimization
  3. Structuring Machine Learning Projects
  4. Convolutional Neural Networks
  5. Sequence Models
• TensorFlow in Practice Specialization
  1. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
  2. Convolutional Neural Networks in TensorFlow
  3. Natural Language Processing in TensorFlow
  4. Sequences, Time Series and Prediction
• TensorFlow: Data and Deployment Specialization
  1. Browser-based Models with TensorFlow.js
  2. Device-based Models with TensorFlow Lite
  3. Data Pipelines with TensorFlow Data Services
  4. Advanced Deployment Scenarios with TensorFlow
• Mathematics for Machine Learning
  1. Mathematics for Machine Learning: Linear Algebra
  2. Mathematics for Machine Learning: Multivariate Calculus
  3. Mathematics for Machine Learning: PCA
• Applied Data Science Specialization
  1. Python for Data Science and AI
  2. Data Analysis with Python
  3. Data Visualization with Python
  4. Applied Data Science Capstone
• IBM Data Science Professional Certificate
  1. What is Data Science?
  2. Open Source tools for Data Science
  3. Data Science Methodology
  4. Python for Data Science and AI
  5. Databases and SQL for Data Science
  6. Data Analysis with Python
  7. Data Visualization with Python
  8. Machine Learning with Python
  9. Applied Data Science Capstone
• AWS Builders Online Series
  1. Introductory Guide to AWS Cost Management and Efficiency
  2. Move Fast & Be Secure on AWS Cloud
  3. AWS Purpose-Built Database Strategy: The Right Tool for The Right Job
  4. Host your Static Website on Amazon Simple Storage Service (S3)
  5. Building Serverless Applications that Scale
• Data Engineering, Big Data, and Machine Learning on GCP Specialization
  1. Google Cloud Platform Big Data and Machine Learning Fundamentals
  2. Modernizing Data Lakes and Data Warehouses with GCP
  3. Building Batch Data Pipelines on GCP
  4. Building Resilient Streaming Analytics Systems on GCP
  5. Smart Analytics, Machine Learning, and AI on GCP
• Deep Neural Networks with PyTorch
• Natural Language Processing Specialization
  1. Natural Language Processing with Classification and Vector Spaces
  2. Natural Language Processing with Probabilistic Models
  3. Natural Language Processing with Sequence Models
  4. Natural Language Processing with Attention Models
• Data Scientist
  1. Fundamentals of the Databricks Lakehouse Platform Accreditation
     • Fundamentals of Delta Lake
     • Fundamentals of Lakehouse Architecture
     • Fundamentals of Databricks SQL
     • Fundamentals of Databricks Machine Learning
     • Fundamentals of Big Data
     • Fundamentals of Machine Learning
     • Fundamentals of Enterprise Data Management Systems
     • Fundamentals of Structured Streaming
  2. Apache Spark Associate Developer
     • Databricks with R
     • Delta Lake Rapid Start with Python
     • Delta Lake Rapid Start with Spark SQL
     • Quick Reference: Spark Architecture
     • Just Enough Python for Apache Spark™
     • Quick Reference: Databricks Workspace User Interface
     • Quick Reference: Managing Databricks Notebooks with the Databricks Workspace
     • Quick Reference: Relational Entities on Databricks
     • What's New In Apache Spark 3.0
     • Certification Prep Course for the Databricks Certified Associate Developer for Apache Spark Exam
  3. Data Science Professional
     • Scalable Machine Learning with Apache Spark
     • Data Science on Databricks Rapidstart
     • Data Science on Databricks: The Bias-Variance Tradeoff
     • Deploying a Machine Learning Project with MLflow Projects
     • Introduction to Applied Linear Models
     • Introduction to Applied Statistics
     • Introduction to Applied Tree-based Models
     • Introduction to Applied Unsupervised Learning
     • Introduction to AutoML
     • Introduction to Databricks Machine Learning
     • Introduction to Databricks Repos
     • Introduction to Feature Engineering and Selection
     • Introduction to Hyperparameter Optimization
     • Introduction to Natural Language Processing
     • Lakehouse with Delta Lake Deep Dive
     • Natural Language Processing with Databricks
     • Tracking Experiments with MLflow
  4. Apache Spark Programming with Databricks