Coursera Machine Learning Certifications Repository

Welcome to the Coursera Machine Learning Certifications Repository! This repository contains the submission labs/notebooks of various machine learning certifications I have completed via Coursera and offered by different major insitutions: DeepLearning.AI, Stanford University and AWS.

Fair Usage Notice

Copying and pasting solutions directly from this repository for your own submissions on Coursera is against the honor code and terms of service of the platform. It is essential to uphold the principles of fairness, honesty, and integrity when undertaking online courses.

Why is Fair Usage Important?

1. Honor Code Violation: Copying solutions without understanding or contributing to them is a direct violation of the honor code of Coursera and can lead to severe consequences.

2. Learning Experience: The primary purpose of these assignments is to enhance your learning experience. Copying solutions hinders your growth and understanding of the subject matter.

3. Build Your Own Skills: Attempting the assignments on your own helps you build crucial problem-solving and coding skills, which are essential in the real-world application of machine learning.

Note on Ownership

The original notebooks belong to the institutions that offer these certifications under the MIT license. These notebooks are my submissions to the practical labs to complete these certifications.

Your Responsibility

By using this repository, you acknowledge the importance of fair usage, agree to uphold the integrity of the learning process on Coursera, and recognize the ownership of the institutions over the content. Remember, the knowledge gained through these courses is more valuable than any certificate.

Certifications

1. Machine Learning Specialization

• Instructor: Andrew Ng, Geoff Ladwig, Aarti Bagul and Eddy Shyu

• Offered by: Stanford University & DeepLearning.AI

• Gained Skills:

  • Build ML models with NumPy (from scratch) & scikit-learn
  • Train supervised models for prediction & binary classification tasks
  • Build neural networks with TensorFlow for multi-class classification
  • Use decision trees & tree ensemble methods
  • Apply best practices for ML development
  • Use unsupervised learning techniques for clustering & anomaly detection
  • Build recommender systems with collaborative filtering & deep learning
  • Build a deep reinforcement learning model

• Courses:

  1. Supervised Machine Learning: Regression and Classification
  2. Advanced Learning Algorithms
  3. Unsupervised Learning, Recommenders, Reinforcement Learning

• Certification Link

2. Generative AI with Large Language Models (LLMs)

• Instructors: Antje Barth, Shelbee Eigenbrode, Mike Chambers and Chris Fregly

• Offered by: DeepLearning.AI and AWS

• Course: Generative AI with Large Language Models (LLMs).

• Gained Skills:

  • Gain foundational knowledge and practical skills in generative AI: Prompt Engineering, Finetuning techniques, Reinforcement Learning from Human Feedback (RLHF).
  • Dive into the latest research on Gen AI and its real-world applications.
  • Receive instruction from expert AWS AI practitioners actively building and deploying AI in business use-cases.

• Certification Link

3. DeepLearning.AI TensorFlow Developer Professional Certificate

• Instructor: Laurence Moroney

• Offered by: DeepLearning.AI

• Gained Skills:

  • Best practices for TensorFlow in computer vision applications.
  • Handling real-world image data and strategies to prevent overfitting.
  • Building natural language processing systems using TensorFlow.
  • Applying RNNs, GRUs, and LSTMs for text-based tasks.

• Courses:

  1. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
  2. Convolutional Neural Networks in TensorFlow
  3. Natural Language Processing with TensorFlow
  4. Sequences, Time Series, and Prediction

• Certification Link

4. IBM AI Engineer Professional Certification

• Instructors: Romeo Kienzler, Joseph Santarcangelo, Alex Aklson, SAEED AGHABOZORGI, Samaya Madhavan, Aije Egwaikhide, JEREMY NILMEIER

• Offered by: IBM

• Gained Skills:

  • Artificial Intelligence (AI) , Deep Learning and Machine Learning.
  • Computer Vision, Image Processing, Object Detection
  • Tensorflow, Keras and PyTorch
  • OpenCV, SciPy and scikit-learn

• Courses:

  1. Machine Learning with Python
  2. Introduction to Deep Learning & Neural Networks with Keras
  3. Introduction to Computer Vision and Image Processing
  4. Deep Neural Networks with PyTorch
  5. Building Deep Learning Models with TensorFlow
  6. AI Capstone Project with Deep Learning

• Certification Link

5. Deep Learning Specialization

• Instructors: Andrew Ng, Younes Bensouda Mourri, and Kian Katanforoosh

• Offered by: DeepLearning.AI

• Gained Skills:

  • Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks, and apply deep learning to various applications.
  • Train test sets, analyze variance for deep learning applications, use standard techniques and optimization algorithms, and implement neural networks in TensorFlow.
  • Build convolutional neural networks (CNNs) and apply them to detection and recognition tasks, utilize neural style transfer techniques to generate art, and apply algorithms to process image and video data.
  • Build and train recurrent neural networks (RNNs), work with natural language processing (NLP) tasks and word embeddings, and utilize HuggingFace tokenizers and transformer models for named entity recognition (NER) and question answering.

• Courses:

  1. Neural Networks and Deep Learning
  2. Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization
  3. Structuring Machine Learning Projects
  4. Convolutional Neural Networks
  5. Sequence Models

• Certification Link

Build Your Career in AI and Data Science

If you are passionate about building a successful career in Artificial Intelligence and Data Science, I highly recommend enrolling in the courses mentioned in this repository. These certifications, offered by renowned institutions and expert instructors, cover a wide range of topics and provide hands-on experience to sharpen your skills.