Difference between revisions of "CV - Courses"

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See the complete cou{{#lst:CV|cv-contact}}
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{{#lst:CV|cv-courses_title}}
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<section begin=cv-courses />
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{| style="color: black; background-color: white; width: 100%; padding: 0px 0px 0px 0px; border:0px solid #ddddff;"
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<!--begin--=======================================================================-->
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<ul style="padding-left:23px;">
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<li style="margin-bottom: 3px; font-size:13pt; font-weight:bold">
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''[https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ Python for Data Science and Machine Learning Bootcamp, Udemy]''
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</li>
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<p style="margin-bottom: 5px; margin-left: 20px">
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'''Course content'''
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</p>
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</ul>
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{|
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|-
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|
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<li style="margin-bottom: 5px; margin-left: 75px">
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NumPy and Pandas
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</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
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Python for Data Visualization:
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</li>
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<li style="margin-bottom: 5px; margin-left: 100px">
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Matplotlib, Seaborn, Pandas Built-in-Data Visualization
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</li>
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<li style="margin-bottom: 5px; margin-left: 100px">
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Plotly and Cufflinks
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</li>
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<li style="margin-bottom: 10px; margin-left: 100px">
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Geographical Plotting
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</li>
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|
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<li style="margin-bottom: 5px; margin-left: 75px">
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Linear Regression
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</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
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Cross Validation and Bias-Variance Trade-Off
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</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
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K Nearest Neighbors
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</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
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Decision Tress and Random Forests
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</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
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Support Vector Machines
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</li>
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|
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<li style="margin-bottom: 5px; margin-left: 75px">
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K Means Clustering
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</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
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Principal Component Analysis
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</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
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Recommender Systems
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</li>
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<li style="margin-bottom: 0px; margin-left: 75px">
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Natural Language Processing
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</li>
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<div style="margin-bottom: 5px; margin-left: 100px; color:white">
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.
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</div>
 
|}
 
|}
  
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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/
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</p>
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</ul>
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<ul style="padding-left:23px;">
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<li style="margin-bottom: 3px; font-size:13pt; font-weight:bold">
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''[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/
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</p>
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</ul>
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<ul style="padding-left:23px;">
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<li style="margin-bottom: 3px; font-size:13pt; font-weight:bold">
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''[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'''
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</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">
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AWS CloudFormation Templates
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</li>
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<div style="margin-bottom: 5px; margin-left: 100px; color:white">
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.
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</div>
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|
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<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>
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|
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<li style="margin-bottom: 5px; margin-left: 75px">
 +
Multi-region failover with Amazon Route 53
 +
</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
 +
 +
</li>
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<li style="margin-bottom: 5px; margin-left: 75px">
 +
 +
</li>
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<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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<!--end--=========================================================================-->
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|-
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|}
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<section end=cv-courses />
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rse content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
 
</p>
 
</p>
 
</ul>
 
</ul>

Revision as of 20:40, 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
    • See the complete cou

      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


    • rse content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/