Difference between revisions of "CV - Courses"

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NumPy and Pandas
 
NumPy and Pandas
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Designing a cloud environment
 
Designing a cloud environment
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See the complete cou{{#lst:CV|cv-contact}}
 
 
 
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{| style="color: black; background-color: white; width: 70%; padding: 0px 0px 0px 0px; border:0px solid #ddddff;"
 
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<ul style="padding-left:23px;">
 
<li style="margin-bottom: 3px; font-size:13pt; font-weight:bold">
 
''[https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ Python for Data Science and Machine Learning Bootcamp, Udemy]''
 
</li>
 
<p style="margin-bottom: 5px; margin-left: 20px">
 
'''Course content'''
 
</p>
 
</ul>
 
{|
 
|-
 
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<li style="margin-bottom: 5px; margin-left: 75px">
 
NumPy and Pandas
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Python for Data Visualization:
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Matplotlib, Seaborn, Pandas Built-in-Data Visualization
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Plotly and Cufflinks
 
</li>
 
<li style="margin-bottom: 10px; margin-left: 100px">
 
Geographical Plotting
 
</li>
 
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<li style="margin-bottom: 5px; margin-left: 75px">
 
Linear Regression
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Cross Validation and Bias-Variance Trade-Off
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
K Nearest Neighbors
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Decision Tress and Random Forests
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Support Vector Machines
 
</li>
 
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<li style="margin-bottom: 5px; margin-left: 75px">
 
K Means Clustering
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Principal Component Analysis
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Recommender Systems
 
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<li style="margin-bottom: 0px; margin-left: 75px">
 
Natural Language Processing
 
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.
 
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<p style="margin-bottom: 10px; margin-left: 52px">
 
<p style="margin-bottom: 10px; margin-left: 52px">
 
See the complete course content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
 
See the complete course content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
</p>
 
</ul>
 
 
 
<ul style="padding-left:23px;">
 
<li style="margin-bottom: 3px; font-size:13pt; font-weight:bold">
 
''[https://www.udemy.com/course/interactive-python-dashboards-with-plotly-and-dash/ Interactive Python Dashboards with Plotly and Dash]''
 
</li>
 
<p style="margin-bottom: 5px; margin-left: 20px">
 
See course content at https://www.udemy.com/course/interactive-python-dashboards-with-plotly-and-dash/
 
</p>
 
</ul>
 
 
 
<ul style="padding-left:23px;">
 
<li style="margin-bottom: 3px; font-size:13pt; font-weight:bold">
 
''[https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ AWS Academy - Cloud Architecting]''
 
</li>
 
<p style="margin-bottom: 5px; margin-left: 20px">
 
'''Course content'''
 
</p>
 
</ul>
 
{|
 
|-
 
|
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Designing a cloud environment
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Designing for High Availability
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Configuring VPS, Availability zones, NAT Gateway, Route Table, Load Balancer, Auto Scaling Group.
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Automating your Infrastructure
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Infrastructure as code
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
AWS CloudFormation Templates
 
</li>
 
<div style="margin-bottom: 5px; margin-left: 100px; color:white">
 
.
 
</div>
 
|
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Decoupling your Infrastructure
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Loose coupling Strategies
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Designing Web Scale Media
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Storing Web-Accessible Content with Amazon S3
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Caching with Amazon CloudFront
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 100px">
 
Storing relational data in Amazon RDS, Managing NoSQL databases
 
</li>
 
|
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
Multi-region failover with Amazon Route 53
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
 
</li>
 
<li style="margin-bottom: 5px; margin-left: 75px">
 
 
</li>
 
<li style="margin-bottom: 0px; margin-left: 75px">
 
 
</li>
 
|}
 
 
<ul style="padding-left:10px;">
 
<p style="margin-bottom: 10px; margin-left: 52px">
 
See the complete course content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
 
</p>
 
</ul>
 
 
 
 
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<section end=cv-courses />
 
rse content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
 
 
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</p>
 
</ul>
 
</ul>

Revision as of 19:56, 13 January 2021

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).





  • 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
  • .



    • 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