MOOCs

Massive Open Online Courses (MOOCs) are free online courses available for anyone to enroll. I have completed or enrolled in following MOOCS:

Datacamp

https://www.datacamp.com/portfolio/umermajeed

• Introduction to Python - Completed with certificate - 2017 -

• Intermediate Python - Completed with certificate - 2017 -

• Data Types for Data Science in Python - Completed with certificate - 2017 -

• Python Data Science Toolbox (Part 1) - Completed with certificate - 2017 -

• Python Data Science Toolbox (Part 2) - Completed with certificate - 2017 -

• Statistical Thinking in Python (Part 1) - Completed with certificate - 2017 -

• Statistical Thinking in Python (Part 2) - Completed with certificate - 2017 -

• Introduction to Version Control with Git - Completed with certificate - 2018 -

• Intermediate SQL Queries - Completed with certificate - 2017 -

• Introduction to Shell - Completed with certificate - 2018 -

• Introduction to Data Visualization in Python - Completed with certificate - 2017 -

• Intermediate Data Visualization with Seaborn - Completed with certificate - 2018 -

Private & Secure AI and Data Science

1. Our Privacy Opportunity by openmined.org - Completed with certificate awaiting - Mar. 2021
   Explore structured transparency, privacy techniques, and the privacy-transparency trade-off.

2. Foundations of Private Computation by openmined.org - In Progress - Progress 80%
   Implement federated learning, secure multi-party computation, homomorphic encryption, and differential privacy.

3. Introduction to Remote Data Science by openmined.org - Completed with certificate awaiting - Feb. 2022
   Use remote execution tools, deploy Domain Nodes, and apply privacy-preserving techniques for distributed data science.

Blockchain, Smart Contracts and Web3

Blockchain Specialization - Coursera

Blockchain Specialization - University at Buffalo - Coursera - Completed with certificate - Feb. 2020 -

• Blockchain Basics - Completed with certificate - Dec. 2018 -
  Understand the core principles of blockchain technology, including its structure, cryptographic security, and consensus mechanisms like PoW and PoS.

• Smart Contracts - Completed with certificate - July 2019 -
  Learn to design, code, and deploy smart contracts using Solidity, and implement best practices for secure and efficient contract development.

• Decentralized Applications (Dapps) - Completed with certificate - Jan. 2020 -
  Develop end-to-end Dapps, integrate with front-end interfaces using MetaMask, and deploy using Truffle Suite.

• Blockchain Platforms - Completed with certificate - Feb. 2020 -
  Explore platforms like Hyperledger Fabric and Microsoft Azure, and analyze decentralized solutions like IPFS and Hashgraph.

IBM Blockchain Foundation for Developers - Course - Coursera

• IBM Blockchain Foundation for Developers by IBM - Coursera Completed with certificate - Aug. 2018 -
  This course provides a comprehensive overview of business networks utilizing blockchain technology, emphasizing Hyperledger Composer and Hyperledger Fabric. Participants learn about essential concepts, key use cases, and the process of transferring assets within a blockchain network. The course also covers access control mechanisms, network consensus methods, and the roles and responsibilities of individuals involved in building and maintaining a blockchain business network.

• Ethereum Developer Degree by learnweb3.io
  

  • Freshman Graduate See Compeletion NFT on Opensea - Fundamentals of blockchain, Ethereum, and Solidity for building dApps and understanding decentralized systems.
  • Sophomore Graduate See Compeletion NFT on Opensea - Deep understanding of gas, mining, PoW, PoS, and EVM. Learn to build full dApps with custom contracts, NFTs, DAOs, ICOs, and DEXs using React and Next.js.
  • Junior - In progress -Exploring Layer 2 solutions, ENS integration, local smart contract testing, IPFS, Ceramic, Chainlink VRF, and The Graph’s Indexer.
  • Senior - In progress - Mastering advanced Web3 topics including Merkle Trees, Flash Loans, Smart Contract Security, MEV, and Gas Optimization.

Web3 and Blockchain Fundamentals - Course - Coursera

• Web3 and Blockchain Fundamentals by INSEAD - Coursera Audit Completed - Feb. 2024
  This course covers essential concepts in Web3, including the foundational technologies that support decentralized applications, the roles of smart contracts, digital assets, and governance tokens within the ecosystem. Participants explore the implications of DAOs (Decentralized Autonomous Organizations) and identify key blockchain design principles along with the challenges associated with implementing blockchain technology in real-world scenarios.

Solidity, Blockchain, and Smart Contract Course – Beginner to Expert Python Tutorial

• Solidity, Blockchain, and Smart Contract Course – Beginner to Expert Python Tutorial by freeCodeCamp.org
  In progress
  The blockchain course introduces participants to foundational concepts such as blockchain technology, Ethereum and Bitcoin, and essential components like smart contracts and oracles. Students learn to utilize Metamask for transactions, navigate Ethereum testnets, and understand gas fees and consensus mechanisms. The curriculum progresses from basic Solidity programming and deploying contracts to more advanced topics like building funding contracts and decentralized applications (dApps). Participants gain practical experience using frameworks like Brownie and Web3.py, exploring features like Chainlink oracles, ERC20 token standards, and decentralized finance (DeFi) applications. The lessons also cover advanced concepts, including the creation of Non-Fungible Tokens (NFTs) and the upgradeability of smart contracts, preparing students for practical applications in the decentralized ecosystem.

Artificial Intilligence

Deep Learning Specialization - Coursera

Deep Learning Specialization - Coursera by deeplearning.ai

• Neural Networks and Deep Learning - Completed with certificate - July 2021 -
  Gain a deep understanding of neural networks, implement architectures, and optimize through hyperparameter tuning and regularization.

• Improving Deep Neural Networks - Completed with certificate - August 2021 -
  Explore advanced techniques like hyperparameter tuning, optimization algorithms (Adam, RMSprop), regularization methods (dropout, batch normalization), and implement models using TensorFlow.

• Structuring Machine Learning Projects - Completed with certificate - Oct. 2021 -
  Diagnose errors in ML systems, implement strategies like end-to-end learning and transfer learning, and set human-level performance benchmarks for complex tasks.

• Convolutional Neural Networks - Completed with certificate - Oct. 2021 -

  Explore CNN layers, advanced architectures like ResNet, apply object detection techniques (YOLO, U-Net), and create models for applications like face recognition and neural style transfer.

• Sequence Models - In progress
  Implement RNNs, GRUs, LSTMs, and transformers for NLP tasks like machine translation and named entity recognition, and apply attention mechanisms for enhanced performance.

AI For Everyone - Course - Coursera

• AI For Everyone by deeplearning.ai - Coursera - Completed with certificate - Dec. 2019 -
  This course provides a comprehensive introduction to artificial intelligence (AI), focusing on its applications, impact on society, and essential concepts such as machine learning, deep learning, and data science. Participants will gain an understanding of how AI can be utilized in various industries and its relevance in the modern world.

Fundamentals of Reinforcement Learning - Course - Coursera

• Fundamentals of Reinforcement Learning by UNIVERSITY OF ALBERTA, ALBERTA MACHINE INTELLIGENCE INSTITUTE - from Reinforcement Learning Specialization- Coursera Completed with certificate - Dec. 2020 -
  This course introduces the core principles of reinforcement learning, covering key topics such as Markov decision processes, value functions, and policy gradients. Learners will explore fundamental algorithms and techniques used in reinforcement learning, gaining practical experience through programming assignments and projects.

Data Science

IBM Data Science Professional Certificate - Coursera

IBM Data Science Professional Certificate - Coursera - Audit Completed with Labs - Aug. 2024

• What is Data Science? - April, 2024 - Audit Completed with Labs
  Understand data science fundamentals, career paths, big data processing, ETL, and data pipelines. Gain insights into data science applications and cloud computing.

• Tools for Data Science - April, 2024 - Audit Completed with Labs
  Explore tools for data management, integration, visualization, model building, and deployment. Learn about popular open-source and cloud-based tools.

• Data Science Methodology - April, 2024 - Audit Completed with Labs
  Apply CRISP-DM methodology to structure projects, prepare data, build and evaluate models, and understand iterative improvements.

• Python for Data Science, AI & Development - April, 2024 - Audit Completed with Labs
  Learn Python basics, data structures, Pandas, Numpy, web scraping, REST APIs, and data collection methods.

• Python Project for Data Science - April, 2024 - Audit Completed with Labs
  Extract and analyze stock data using Python, build dashboards to visualize trends, and demonstrate proficiency in data analysis projects.

• Databases and SQL for Data Science with Python - May, 2024 - Audit Completed with Labs
  Learn SQL from basics to advanced, integrate with Python, and work with real-world datasets. Explore relational and cloud databases.

• Data Analysis with Python - May, 2024 - Audit Completed with Labs
  Develop skills in data cleaning, exploratory data analysis, and visualization. Build and evaluate ML models, and create efficient data pipelines.

• Data Visualization with Python - June, 2024 - Audit Completed with Labs
  Implement data visualization techniques with libraries such as Matplotlib and Plotly, build interactive dashboards, and apply skills through hands-on projects.

• Machine Learning with Python - June, 2024 - Audit Completed with Labs
  Study machine learning fundamentals, including regression, classification, and clustering methods. Gain practical experience with Python libraries and complete a final project to showcase your skills.

• Applied Data Science Capstone - August, 2024 - Audit Completed with Labs
  Perform data collection, wrangling, exploratory analysis, and model evaluation using real-world datasets, specifically predicting Falcon 9 rocket landings.

• Generative AI: Elevate Your Data Science Career - July, 2024 - Audit Completed with Labs
  Learn generative AI tools for data preparation and querying, engage in hands-on labs, explore real-world use cases, and understand ethical considerations in data science.

• Data Scientist Career Guide and Interview Preparation - August, 2024 - Audit Completed with Labs
  Prepare for a career in data science by learning about the role of a data scientist, building a job search foundation, creating essential job-seeking materials, and mastering interview preparation techniques.

IBM Data Analyst Professional Certificate - Coursera

IBM Data Analyst Professional Certificate - Coursera

• Introduction to Data Analytics - Sep, 2024 - Audit Completed with Labs
  Learn the fundamentals of Data Analytics, different data roles, data structures, the analysis process, and tools for data gathering and visualization.

• Excel Basics for Data Analysis - Sep, 2024 - Audit Completed with Labs
  Gain insight into Excel for data analysis, including data cleaning, filtering, sorting, and pivot tables.

• Data Visualization and Dashboards with Excel and Cognos - Sep, 2024 - Audit Completed with Labs
  Create basic and advanced visualizations using Excel and Cognos Analytics, including interactive dashboards, to effectively communicate data-driven stories.

• Generative AI: Enhance your Data Analytics Career - Sep, 2024 - Audit Completed with Labs
  Describe how to use Generative AI tools in data analytics, implement data analytic processes, evaluate case studies, and analyze ethical considerations.

• Data Analyst Career Guide and Interview Preparation - Oct, 2024 - Audit Completed with Labs
  Prepare for data analyst job applications, build portfolios, resumes, and cover letters, practice interviews, coding challenges, and hands-on labs (SQL and Python).

• IBM Data Analyst Capstone Project - In progress

  Apply data analysis techniques such as data collection, wrangling, visualization, and dashboard creation using Python, SQL, Cognos, and various libraries to solve real-world business challenges.

The Data Scientist’s Toolbox - Course - Coursera

• The Data Scientist’s Toolbox by Johns Hopkins University - from Data Science Specialization with R- Coursera
  Completed with certificate -
  This course introduces the main tools and ideas in the data science toolbox, providing an overview of the essential data, questions, and tools used by data analysts and scientists. It combines a conceptual understanding of how to transform data into actionable knowledge with practical skills in tools like R, RStudio, Git, and GitHub. Learners will set up these tools, create a GitHub repository, and understand crucial concepts such as experimental design and big data.

Programming

• Crash Course on Python by Google - Coursera - Completed with certificate - March 2020 -
  This course offers a comprehensive introduction to Python syntax, focusing on programming fundamentals and automation tasks relevant to IT roles. Participants learn about essential concepts such as Python automation, code reuse, and refactoring. The curriculum covers error handling techniques and includes a structured problem-solving framework to tackle complex programming challenges. Hands-on exercises enable learners to apply their skills in writing efficient Python scripts and manipulating data effectively.

• Introduction to C++ by Microsoft - edX - Completed with certificate - Dec. 2015 -
  This course covers the fundamentals of C++, including data types, control statements, functions, and object-oriented programming concepts. It begins with an overview of C++ and progresses through essential topics such as portability, compiling, variables, constants, operators, decision-making, and encapsulation.