A𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁 𝘂𝗻𝗹𝗼𝗰𝗸𝗲𝗱! 🔓

Today, I am celebrating the small achievement of reaching the goal of 60 courses with over 80 certifications on LinkedIn. It was a journey of more than 3500 minutes of coursework and at least twice the amount of study time mostly focusing on the main topics of data science, data engineering, data analysis, machine learning, and big data. On this occasion, I want to thank some special people who contributed to my new skills and knowledge. (Certificates may be seen on my home page)

List of some courses that I've finished:

1. Data Engineering Path

• Apache Spark Essential Training: Big Data Engineering ( Kumaran Ponnambalam )
• NoSQL Essential Training (Melanie McGee )

2. Big Data Path

• Big Data in the Age of AI (Barton Poulson)
• Learning Data Governance (Jonathan Reichental)

3. Data Analysis

• The Non-Technical Skills of Effective Data Scientists (Keith McCormick)
• Learning Excel: Data Analysis (Curt Frye)
• Data Fluency: Exploring and Describing Data (2019) (Barton Poulson)
• Learning Data Analytics: 1 Foundation (Robin Hunt)
• Learning Data Analytics Part 2: Extending and Applying Core Knowledge (Robin Hunt)
• Excel Statistics Essential Training: 1 ( Joseph Schmuller )
• Predictive Analytics Essential Training: Data Mining (Keith McCormick)
• Power BI Essential Training (Gini von Courter @ginicourter)
• Learning Data Visualization (Bill Shander @billshander)
• Tableau Essential Training (2021) (Curt Frye)
• SQL: Data Reporting and Analysis (2019) (Emma Saunders)
• R Essential Training: Wrangling and Visualizing Data (Barton Poulson)
• Data Cleaning in Python Essential Training (Miki Tebeka)
• SQL for Exploratory Data Analysis Essential Training (Dan Sullivan)
• Data Visualization: Storytelling(Bill Shander @billshander)

4. Machine Learning

• Artificial Intelligence Foundations: Thinking Machines (Doug Rose)
• Artificial Intelligence Foundations: Machine Learning (Doug Rose)
• Machine Learning with Python: Foundations (Frederick Nwanganga)
• Deep Learning: Getting Started ( Kumaran Ponnambalam )
• Reinforcement Learning Foundations ( Khaulat Abdulhakeem )
• Building and Deploying Deep Learning Applications with TensorFlow (Adam Geitgey)
• Training Neural Networks in Python ( Eduardo Corpeño)
• Developing Chatbots with Azure (Bhavani Ravi)

5- Python for Data Science

• Python for Data Science Essential Training Part 1 (Lillian Pierson)
• Python for Data Science Essential Training Part 2 (Lillian Pierson)
• Data Science Foundations: Python Scientific Stack (Miki Tebeka)
• Python Data Analysis (Michele Vallisneri)

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