Resume_Shourya

My Certifications.

Google Certified - Associate Cloud Engineer

An Associate Cloud Engineer deploys applications, monitors operations, and manages enterprise solutions. Thus, I am able to use Google Cloud Console and the command-line interface to perform common platform-based tasks to maintain one or more deployed solutions that leverage Google-managed or self-managed services on Google Cloud.

Google Certified - Professional Cloud Architect

A Google Cloud Certified - Professional Cloud Architect enables organizations to leverage Google Cloud technologies. Through an understanding of cloud architecture and Google technology, we can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.

Hashicorp Certified - TerraForm Associate

This Terraform Associate certification to verify my basic infrastructure automation skills.The Terraform Associate certification is for Cloud Engineers specializing in operations, IT, or development who know the basic concepts and skills associated with open source HashiCorp Terraform.

Azure Fundamentals [AZ-900]

This certification validated my basic knowledge of cloud services and how those services are provided with Azure. I was able to demonstrate a fundamental knowledge of cloud concepts, along with Azure services, workloads, security, privacy, pricing, and support.

Azure AI Fundamentals [AI-900]

Az AI Fundamentals certification build, manage, and deploy AI solutions that leverage Azure Cognitive Services and Azure Applied AI services. Our responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.

Machine Learning Foundations

Machine learning uses two types of techniques: one is supervised learning which trains a model on known input and output data so that it can predict future outputs. The second called unsupervised learning finds hidden patterns or intrinsic structures in input data. In this course, I learnt some of the most popular supervised learning algorithms such as KNN and Naive Bayes.

Python Basics

It covers topics like Scalar Types, Operators and Control Flow, Strings, Collections and Iteration, Modularity, Objects and Types and Classes

Data Visualization in Python

This course covers Data Visualization in Python, where I was introduced to Python packages, such as NumPy, Pandas, Matplotlib, Seaborn, and Plotly. These packages will allow us to create graphs, charts, and other visual representations of data using Python.

Python for ML

This section covers the machine learning basics using Python, some data structures and various ML techniques which are widely used in today's scenerio.

Mobile Machine Learning for Android: Tensorflow & Python

Making android apps based on Machine Learning models which can work on android devices using Tensorflow library.TensorFlow provides a collection of workflows to develop and train models using Python or JavaScript, and to easily deploy in the cloud, on-prem, in the browser etc.

Artificial Intelligence A-Z

This Artificial Intelligence Course helped me understand the basics of artificial intelligence. Here, I had a look at the future of AI and listen to some of the industry experts and learn what they have to say about AI, Machine Learning and Deep Learning and the different algorithms used to build AI models.

My Publication.

Impact of Data Science, Machine Learning & Artificial Intelligence on Humans