CV - Courses

Adelo Vieira,  Developer / Data Scientist 47-A Phibsborough Rd, Dublin   +353 852 40 72 08   adeloaleman@gmail.com  Github            Linkedin          Portfolio          My Wiki         Download a pdf version of my CV

BSc. (Hons) in Information Technology, Geophysical Engineer, and MSc in Petroleum Geosciencewith strong mathematical, problem-solving, and analytical skills. I'm currently particularly interested in Data Analytics and Software Development. Proficient in multiple programming languages, including Python, Java, JavaScript, SQL, and R. I have a huge interest in Machine Learning and Natural Language Processing. I've been recently working in areas such as Text classification and Sentiment Analysis. I have solid knowledge in several ML algorithms (Naive Bayes, Decision Trees, K-Nearest Neighbour) and in Time Series Analysis. I have experience working with Python (Pandas, NLPTK, Scikit-learn, SciPy, Plotly, TextBlob, Vader Sentiment), R, and RapidMiner. Solid experience in Object-oriented programming and Web Development. I have developed several projects using Java, Python, React, Node.js (Express.js), and Dash. I also have advanced experience with Linux (including Shell Scripting) and I have worked with Relational databases (SQL, MySQL, PostgreSQL) and Cloud computing (AWS and Google Cloud).

Relevant courses

• Uno

• Uno punto uno

• Python for Data Science and Machine Learning Bootcamp, Udemy

Content overview

Content overview

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• NumPy and Pandas

• NumPy and Pandas
• Python for Data Visualization:
• Matplotlib, Seaborn, Pandas Built-in-Data Visualization
• Plotly and Cufflinks
• Geographical Plotting

• Linear Regression
• Cross Validation and Bias-Variance Trade-Off
• K Nearest Neighbors
• Decision Tress and Random Forests
• Support Vector Machines

• K Means Clustering
• Principal Component Analysis
• Recommender Systems
• Natural Language Processing

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NumPy and Pandas Python for Data Visualization: Matplotlib, Seaborn, Pandas Built-in-Data Visualization Plotly and Cufflinks Geographical Plotting

Linear Regression Cross Validation and Bias-Variance Trade-Off K Nearest Neighbors Decision Tress and Random Forests Support Vector Machines

K Means Clustering Principal Component Analysis Recommender Systems Natural Language Processing .

See the complete course content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

• Interactive Python Dashboards with Plotly and Dash

See course content at https://www.udemy.com/course/interactive-python-dashboards-with-plotly-and-dash/

• 150+ Exercises - Object Oriented Programming in Python

See course content at https://www.udemy.com/course/exercises-object-oriented-programming-in-python-oop-course/

• AWS Academy - Cloud Foundations

Content overview

Introduction to AWS Cloud Essential Characteristics of cloud computing, Service Model, Deployment Models AWS Global Infrastructure: Regions, Availability zones, Edge Locations .

AWS foundation services: Compute: EC2, AWS Lambda, ECS, Auto Scaling Networking: VPC, Elastic Load Balancer, Route 53 Storage: Amazon EBS, Amazon S3, Amazon EFS, Amazon Relational Database Service (RDS)

• AWS Academy - Cloud Architecting

Content overview

Designing a cloud environment Designing for High Availability Configuring VPS, Availability zones, NAT Gateway, Route Table, Load Balancer, Auto Scaling Group. Automating your Infrastructure Infrastructure as code AWS CloudFormation Templates .

Decoupling your Infrastructure Loose coupling Strategies Designing Web Scale Media Storing Web-Accessible Content with Amazon S3 Caching with Amazon CloudFront Storing relational data in Amazon RDS, Managing NoSQL databases

Multi-region failover with Amazon Route 53 . . . . .