Hello! I am Anass, and I’m passionate about the Cloud with over 5+ years of experience in the field. I have created numerous labs on the cloud and have a strong enthusiasm for networking. For a closer look at my work and projects, please visit my website.
Azure API Management Integration with Azure App Service This project demonstrates how to integrate Azure API Management (APIM) with an Azure App Service-hosted Web API. By leveraging APIM, you can securely expose, manage, and monitor your APIs, while Azure App Service provides a scalable platform for hosting your web...
Azure Data Factory: Dynamic Pipeline Orchestration Overview This project demonstrates the implementation of flexible and dynamic pipelines using Azure Data Factory (ADF) to orchestrate and automate data movement and transformation across various services, including Azure Blob Storage and Azure SQL Database. Architecture Tech Stack Azure Data Factory Azure...
Successfully deployed a Nextcloud server on an Azure Virtual Machine, demonstrating proficiency in Azure's core architecture. This project involved creating and configuring a Virtual Network with subnets, implementing Network Security Groups to enforce security policies, and using Azure Bastion for secure SSH access. Additionally, i installed and configured the Nextcloud...
Executed API calls to generate predictions, utilizing the Microsoft API portal for demonstration. Gained hands-on experience in creating Resource Groups and identifying API keys and URLs. Learned to interpret API call results and understood the differences between synchronous and asynchronous operations. Explored various Computer Vision APIs and their integration into...
I designed and managed the deployment of a high-availability web application leveraging AWS infrastructure. This involved using VPC for network isolation, EC2 for scalable compute resources, and RDS for reliable database services. I utilized Route 53 for DNS management, ASG for automated scaling, and S3 for backup solutions. Lambda was...
During the Defi IA 2022 with MeteoNet and INSA Toulouse, I utilized MeteoNet data and my expertise in Python to predict daily precipitation. I preprocessed and cleaned data to make it usable, and created a recurrent neural network (RNN) to forecast future precipitation. I adapted the model to the data format for accurate future predictions, leveraging my skills in artificial intelligence (AI), statistical data analysis, and predictive modeling.
During my internship at the Institut de Mathématiques de Toulouse, I analyzed Covid-19 data and collected and preprocessed data from various countries. I developed a regression model and a statistical SIRD (Suspected, Infected, Recovered, Death) model using the implicit Euler method to predict health states. I also used a neural network to predict mortality and recovery rates, leveraging my skills in Keras, Python, recurrent neural networks, crisis management, TensorFlow, mortality analysis, and epidemiology.
I forecasted the values of 14 major cryptocurrencies by developing predictive models from scratch. I utilized Python for data retrieval and preprocessing and created recurrent neural networks (RNNs) to predict cryptocurrency values. Leveraging TensorFlow and Keras, I developed innovative prediction methods and tested them to minimize errors. I validated these methods on real-time data and evaluated results over time, applying skills in Keras, Python, predictive modeling, artificial intelligence (AI), big data, TensorFlow, deep learning, and Apache Spark.
As a Data & Cloud Engineer, I'am responsible for designing, implementing, and managing data and infrastructure solutions on Azure, with a focus on performance, scalability, and security.
Key Responsibilities:
Designed and deployed cloud-based data solutions using Azure services.
Transformed and secured enterprise data while ensuring high availability and optimal performance.
Analyzed business data requirements and proposed scalable architectural solutions.
Contributed to the design and deployment of secure and resilient cloud infrastructure.
Developed robust, scalable, and fault-tolerant data pipelines.
Built ETL/ELT processes for integrating, transforming, and migrating data from multiple sources.
Implemented version control systems and CI/CD pipelines.
Administered and optimized relational and non-relational databases.
Managed Data Lakes and Data Warehouses for large-scale analytics.
Ensured data quality through cleansing, validation, and governance mechanisms.
Monitored data system performance and optimized queries for efficiency.
Applied security best practices, including encryption, access control, and anomaly detection.
Ensured compliance with data protection regulations (GDPR, HIPAA).
Provided technical support and troubleshooting for data and infrastructure solutions across VMs, containers, PaaS, and API Management.
Documented architectures, processes, and implemented solutions.
Maintained effective communication with internal teams and clients.
Clients: GazelEnergie, Unicem
I have tackled intricate mathematical challenges, explored functional analysis and spectral theory, investigated number theory and geometric algebra, conducted descriptive and complex analysis, and studied probability theory and distribution patterns.
I possess expertise in a wide range of applied mathematics, from scientific computing to statistics, with the ability to solve complex engineering and industrial problems using mathematical models and methods. I am proficient in data analysis and big data tools, skilled in creating and optimizing neural networks, and have strong capabilities in probabilities, statistics, and sampling. Additionally, I excel in solving optimization and operational research problems.
