Difference between revisions of "CV - Courses"
Adelo Vieira (talk | contribs) |
Adelo Vieira (talk | contribs) |
||
Line 153: | Line 153: | ||
</li> | </li> | ||
</ul> | </ul> | ||
+ | |} | ||
+ | |||
+ | <ul style="padding-left:10px;"> | ||
+ | <p style="margin-bottom: 10px; margin-left: 52px"> | ||
+ | See the complete cou{{#lst:CV|cv-contact}} | ||
+ | |||
+ | |||
+ | {{#lst:CV|cv-courses_title}} | ||
+ | |||
+ | |||
+ | <section begin=cv-courses /> | ||
+ | {| style="color: black; background-color: white; width: 100%; padding: 0px 0px 0px 0px; border:0px solid #ddddff;" | ||
+ | <!--begin--=======================================================================--> | ||
+ | <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> | ||
+ | {| | ||
+ | |- | ||
+ | | | ||
+ | <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> | ||
+ | | | ||
+ | <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> | ||
+ | | | ||
+ | <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 | ||
+ | </li> | ||
+ | <li style="margin-bottom: 0px; margin-left: 75px"> | ||
+ | Natural Language Processing | ||
+ | </li> | ||
+ | <div style="margin-bottom: 5px; margin-left: 100px; color:white"> | ||
+ | . | ||
+ | </div> | ||
|} | |} | ||
Line 158: | Line 229: | ||
<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> | ||
+ | |||
+ | |||
+ | |||
+ | <!--end--=========================================================================--> | ||
+ | |- | ||
+ | |} | ||
+ | <section end=cv-courses /> | ||
+ | rse content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ | ||
</p> | </p> | ||
</ul> | </ul> |
Revision as of 19:40, 13 January 2021
Adelo Vieira, Developer / Data Scientist 47-A Phibsborough Rd, Dublin
| ||||
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). |
- Python for Data Science and Machine Learning Bootcamp, Udemy
Course content
|
|
. |
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/
- AWS Academy - Cloud Architecting
Course content
. |
|
|
- Python for Data Science and Machine Learning Bootcamp, Udemy
- 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
- Interactive Python Dashboards with Plotly and Dash
- AWS Academy - Cloud Architecting
- 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
| ||||
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). |
Course content
|
|
. |
See the complete course content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
See course content at https://www.udemy.com/course/interactive-python-dashboards-with-plotly-and-dash/
Course content
. |
|
|
See the complete course content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
rse content at https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/