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My Intro

About me

Experience

6 years Working

Completed

32+ Projects

Support

Online 24/7
Contact Me
My abilities

My Experience

DevOps Engineering

Docker

Advanced

Ansible

Intermediate

Jenkins/Azure DevOps

Intermediate

Kubernetes

Advanced

Puppet

Intermediate

AWS/Azure/GCP

Advanced

Site Reliability Engineering

Chef

Advanced

Prometheus

Intermediate

JMeter

Advanced

PagerDuty

Intermediate

OpsGenie

Intermediate

VictorOps

Intermediate

Articial Intelligence

Tensorflow

Advanced

Scikit-learn

Intermediate

Keras

Advanced

Pandas

Intermediate

Matlib

Intermediate

PyTorch

Intermediate

Python Automation

Python

Advanced

Selenium

Intermediate

PyTest

Advanced

Celery

Intermediate

Fabric

Intermediate

Behave

Intermediate
My services

What I Offer

Chatbots

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Chatbots

Design, development, and deployment of chatbots for customer service, marketing, and other use cases.

  • Analyze client requirements and design a chatbot solution that meets their specific needs.

  • Choose an appropriate platform and tools for chatbot development and integration.

  • Implement the chatbot's natural language processing (NLP) and dialog management features.

  • Integrate the chatbot with relevant systems and services, such as customer relationship management (CRM) software or databases.

  • Test the chatbot and make any necessary adjustments to ensure that it functions correctly and meets the client's requirements.

Agile System Engineering for Data Science

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Agile System Engineering for Data Science

Develop and deploy data science solutions in an agile manner. The goal is to quickly bring data science solutions to market while ensuring high quality and scalability.

  • Analyze the requirements of the data science solution and design an architecture that meets the client's needs.

  • Choose appropriate data science tools, such as Python, R, or Spark.

  • Develop the data science solution using an agile development process.

  • Test the data science solution to ensure that it meets the client's requirements.

  • Deploy the data science solution and monitor it to ensure that it is functioning correctly in a production environment.

CI/CD
Pipelines

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CI/CD Pipelines

Design and implementation of continuous integration and continuous deployment pipelines, using tools such as Jenkins, GitLab CI/CD, or Travis CI.

  • Analyze client requirements and design a CI/CD pipeline that meets their specific needs.

  • Choose an appropriate CI/CD tool and configure it to meet the client's requirements.

  • Integrate the CI/CD pipeline with the client's source control management system, such as Git.

  • Automate the building, testing, and deployment of applications and services.

  • Monitor the CI/CD pipeline and make any necessary adjustments to ensure that it functions correctly and meets the client's requirements.

Infrastructure
Automation

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Infrastructure Automation

Automating the provisioning, configuration, and management of infrastructure using tools such as Ansible, Terraform, or CloudFormation.

  • Analyze client requirements and design an infrastructure automation solution that meets their specific needs.

  • Choose an appropriate automation tool, such as Ansible, Terraform, or CloudFormation.

  • Write automation scripts and templates to provision, configure, and manage infrastructure components, such as servers, databases, and storage systems.

  • Test the automation scripts and make any necessary adjustments to ensure that they function correctly and meet the client's requirements.

  • Implement the infrastructure automation solution and ensure that it is functioning correctly.

Deployment
Automation

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Deployment Automation

Automating the deployment of applications and services, using tools such as Docker, Kubernetes, or AWS Elastic Beanstalk.

  • Analyze client requirements and design a deployment automation solution that meets their specific needs.

  • Choose an appropriate deployment tool, such as Docker, Kubernetes, or AWS Elastic Beanstalk.

  • Write automation scripts and templates to deploy and manage applications and services.

  • Test the deployment automation solution and make any necessary adjustments to ensure that it functions correctly and meets the client's requirements.

  • Implement the deployment automation solution and ensure that it is functioning correctly.

Monitoring
and Logging

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Monitoring and Logging

Implementation of monitoring and logging systems, using tools such as Nagios, Logstash, and Kibana, to ensure the availability, performance, and security of applications and services.

  • Analyze client requirements and design a monitoring and logging solution that meets their specific needs.

  • Choose an appropriate monitoring and logging tool, such as Nagios, Logstash, and Kibana.

  • Configure the monitoring and logging tool to monitor the availability, performance, and security of applications and services.

  • Implement the monitoring and logging solution and ensure that it is functioning correctly.

  • Monitor the monitoring and logging solution and make any necessary adjustments to ensure that it continues to meet the client's requirements.

Cloud
Migration

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Cloud Migration

Design and implementation of cloud migration strategies, including the migration of on-premise applications and services to cloud platforms.

  • Analyze client requirements and design a cloud migration plan that meets their specific needs.

  • Choose an appropriate cloud provider and services, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).

  • Develop a migration strategy and plan for moving the client's existing systems and data to the cloud.

  • Execute the migration plan, which may involve moving virtual machines, databases, or other components to the cloud.

  • Validate that the migration was successful and that the client's systems and data are functioning correctly in the cloud.

Software
Testing

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Software Testing

Evaluate the functionality and quality of a software application. The goal is to identify defects or issues before the software is released to the public.

  • Analyze the requirements of the software application and design a testing plan to ensure that it meets the client's needs.

  • Choose an appropriate testing tool, such as Selenium, Appium, or JUnit.

  • Write test cases to validate the functionality of the software application.

  • Execute the test cases and report any defects or issues that are found.

  • Work with the development team to resolve any defects or issues that are found during the testing process.

Security

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Security

Design and implementation of security measures, such as network security, firewall configurations, and access control, to protect against cyber threats.

  • Analyze client requirements and design a security solution that meets their specific needs.

  • Choose an appropriate security tool, such as firewall, intrusion detection system, or vulnerability scanner.

  • Configure the security tool to protect the client's systems and data.

  • Implement the security solution and ensure that it is functioning correctly.

  • Monitor the security solution and make any necessary adjustments to ensure that it continues to meet the client's requirements.

My Portfolio

Recent Works

All Contract Personal

Dathway

Thought Process

Dathway

I need to build a chatbot that can recommend skills based on the user's social activity. Let me think about how to approach this.

  • Me: First, I need to determine the best way to gather social activity data. Should I use social media APIs or web scraping?

  • Me: I think it would be best to use APIs, as web scraping could be unreliable and lead to data privacy issues.

  • Me: Next, I need to determine the criteria for recommending skills. Should I use machine learning or a rule-based approach?

  • Me: I think machine learning would be more accurate, but it would require a lot of data to train the model. Maybe I can start with a simple rule-based approach and then incorporate machine learning later on.

  • Me: Now, I need to decide on the best platform for building the chatbot. Should I use a third-party platform like Dialogflow or build a custom bot with Python?

  • Me: I think building a custom bot with Python would give me more control and flexibility. I can use the Telegram API for messaging and the scikit-learn library for machine learning.

  • Me: Lastly, I need to determine how to deploy the chatbot. Should I use a cloud platform like AWS or deploy it on-premises?Me: Now, I need to decide on the best platform for building the chatbot. Should I use a third-party platform like Dialogflow or build a custom bot with Python?

  • Me: I think using a cloud platform like AWS would be more scalable and cost-effective in the long run. I can use Terraform for infrastructure as code and Jenkins for continuous integration and deployment.

Stackon

Thought Process

Stackon

I need to build a project called Stackon that can predict the future price of non-fungible items. Let me think about how to approach this.

  • First, I need to determine what kind of historical data I can use. Where can I get the necessary information?

  • I think I can get data from online marketplaces and blockchain records. I can use APIs to gather the data and store it in a database.

  • Next, I need to determine what kind of sentimental data I can use. What are some sources of sentimental data?

  • I think I can gather data from social media, forums, and blogs. I can use sentiment analysis tools to determine the overall mood towards a specific NFT.

  • Now, I need to decide on the best algorithm to predict the future price of an NFT. Should I use a linear regression model or a machine learning model?

  • I think I should start with a linear regression model to establish a baseline, then move onto machine learning if necessary. I can use Python and libraries like scikit-learn for this.

  • Lastly, I need to determine how to present the predicted price to users. Should I create a web app or a mobile app?

  • I think creating a web app would be the most accessible and cost-effective solution. I can use Flask to create a simple web application that allows users to input information about an NFT and receive a predicted price. Doing that i will need to deploy a multi-container application using Azure DevOps, Azure Kubernetes Service, Azure Container Registry and Azure SQL Server.

Schooic

Thought Process

Schooic

I need to build a virtual school where AIs can teach users digital skills. What's the best way to go about this?

  • I think the first step is to determine the skills we want to teach. What are some of the most in-demand digital skills?

  • Programming, web development, graphic design, and data analysis are all popular. Let's focus on those.

  • Next, we need to figure out how to train the AIs. Should we use pre-built models or build our own?

  • Building our own models will give us more control and flexibility, but it will also take more time and resources. Maybe we can start with pre-built models and fine-tune them as needed.

  • Okay, so we have our skills and our AIs. How do we deliver the content? Do we use video lessons, live classes, or something else?

  • Live classes would be more engaging and allow students to ask questions in real-time. Let's go with that.

  • Alright, so we have live classes with AI teachers. How do we grade assignments and track progress?

  • We can use machine learning algorithms to grade assignments and track progress over time. We can also give students personalized feedback and recommendations based on their strengths and weaknesses.

  • Great, we have a plan. Now, we need to figure out the technical details. What programming languages, frameworks, and tools should we use?

  • For the AI models, we can use TensorFlow or PyTorch. For the live classes, we can use Zoom or a custom video conferencing tool. For the grading and feedback, we can use scikit-learn or a similar library. We'll also need a web development framework for the Schooic platform itself.

  • And yeah, before i forget i need to create a Big Data Cluster Infrastructure so i can properly manage the tonnes of data i will train the AIs with.

Xposure

Thought Process

Xposure

Alright team, let's talk about the Xposure project. We've decided to build it with StereoKit in C#, using the StereoKitXPlat template.

  • Jack: That's right. And we made sure to use that template so that we can run our app on the StereoKit fallback simulator as well as natively on Quest.

  • Flavius: Using the fallback simulator has been a real time saver for us. We can iterate quickly and make sure everything is working properly before deploying to the Quest.

  • David: And speaking of the Quest, the ability to use Quest + Link with hot reloads has been a game changer. It allows us to test in-headset and make changes quickly.

  • Jack: Absolutely, and we want to make sure we take advantage of all the features that StereoKit has to offer. Let's brainstorm some ideas for how we can really showcase the power of this platform in our app.

  • Flavius: Well, one idea I had was to use the spatial mapping features to create a more immersive experience for the user.

  • David: That's a great idea. We could also use some of the gesture recognition features to allow the user to interact with the app in a more natural way.

  • Jack: And don't forget about the 3D object manipulation features. We could really make the app stand out by allowing the user to manipulate objects in a more intuitive way.

  • Flavius: These are all great ideas. Let's keep brainstorming and see what else we can come up with.

  • David: Let's not forget to provison infrastructure with Terraform on Azure or AWS or GCP. And i think GPU Cluster nodes will do us good.

One2One

Thought Process

One2One

I need to build an API that can handle client requests for a one2one project that connects users with their favorite celebrities. Let me think about how to approach this.

  • First, I need to determine the types of requests that the API will handle. Will it be mostly read requests, write requests, or a combination of both?

  • I think it will be a combination of both, with clients requesting information on available celebrities and submitting requests for booking sessions with them.

  • Next, I need to decide on the best platform for building the API. Should I use a third-party platform like AWS API Gateway or build a custom API with Node.js?

  • I think building a custom API with Node.js would give me more control and flexibility. I can use Express.js for routing and handling requests.

  • Now, I need to determine how to store and manage the data for the celebrities and the sessions. Should I use a NoSQL database like MongoDB or a SQL database like MySQL?

  • I think a NoSQL database like MongoDB would be more flexible for storing the different types of data, and I can use Mongoose for object modeling.

  • Lastly, I need to determine how to deploy and manage the API. Should I use a cloud platform like AWS or deploy it on-premises?

  • I think using a cloud platform like AWS would be more scalable and cost-effective in the long run. I can use Terraform for infrastructure as code and Jenkins for continuous integration and deployment.

Achievements

Awards

Hackathon
Winner

Microsoft DevDays

Hackathon
Winner

EVM x IDEATHON

Hackathon
Mention

Near Metabuild
My clients say

Testimonial

Alex Azzi

A beast, technical and business wise! David understands what he is doing and he is a very intentional young man.

Yousef Rahman

Vibrant young man. Very fast and detailed with machine learing models.

Aida Nassar

I had the pleasure of working on a recent project and was blown away by their skills in Automation. They were able to create an efficient and reliable infrastructure that enabled our work scale largely and perform at its best. I would highly recommend to anyone looking for a top-notch engineer.

Get in touch

Contact Me

Talk to me

Email

hi@dbobola.com Write me

Whatsapp

+234 70 53747657 Write me

Telegram

@david_bobola Write me

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