Python + GCP
Infosys Bengaluru East, Karnataka, India
Job Description
"Unlock the power of Python and Google Cloud Platform to drive innovation and excellence in the machine learning domain."
As an Infosys professional specializing in Python and Google Cloud Platform, you'll embark on a journey to design, develop, and validate cutting-edge machine learning solutions that delight clients and drive business growth.
Your expertise will be pivotal in translating client requirements into system requirements, ensuring seamless project estimations, and delivering high-quality technology services that exceed expectations.
Why you should learn this:
The demand for Python and Google Cloud Platform skills is skyrocketing, with 85% of companies planning to adopt cloud technologies by 2025.
Expected Salary: With an average salary range of $120,000 - $180,000, Python and Google Cloud Platform professionals are in high demand and highly compensated.
How it works:
- Step 1: Design and Develop Machine Learning Models using Python, leveraging popular libraries like TensorFlow and PyTorch.
- Step 2: Deploy and Manage Machine Learning Workloads on Google Cloud Platform, utilizing Compute, Networking, Storage & Databases services.
Core Concepts to Master
Google Cloud Platform Fundamentals
Understand the core concepts of Google Cloud Platform, including Compute Engine, Cloud Storage, Cloud Datastore, and Cloud SQL.
Python Machine Learning Essentials
Master the fundamentals of Python machine learning, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
Google Cloud AI Platform
Learn to deploy, manage, and monitor machine learning models on Google Cloud AI Platform, utilizing AutoML and Custom ML.
Interview Questions (Beginner)
- What is the difference between supervised and unsupervised machine learning?
- How do you handle missing values in a dataset?
- What is the purpose of feature scaling in machine learning?
Job Overview
Advance Questions
- • How do you optimize the hyperparameters of a machine learning model?
- • What is the difference between a neural network and a decision tree?
- • How do you evaluate the performance of a machine learning model?