Gajesh Ladhar

Gajesh Ladhar has a diverse work experience in the field of data science, artificial intelligence, and backend development. Gajesh started their career as a Blockchain Researcher at Veermata Jijabai Technological Institute (VJTI) in 2019. Later in 2020, they worked as a Machine Learning Engineer Intern at Pianalytix and as a Backend Developer Intern at SoftEzi Solutions LLP. In 2021, they joined Intensel Limited as an Artificial Intelligence Engineer, where they worked until 2023. Currently, they hold the position of Data Scientist-3 at SatSure.

Gajesh Ladhar's education history is as follows:

Gajesh Ladhar completed a program in Data Science and Machine Learning from Scaler in the year 2023.

From 2017 to 2021, Gajesh Ladhar pursued a Bachelor's degree in Computer Science from Rajasthan Technical University.

In 2016, Gajesh Ladhar completed their Senior Secondary (12th) education from the Board of Secondary Education Rajasthan, with a focus in Science.

In 2014, Gajesh Ladhar completed their Secondary (10th) education from the Board of Secondary Education Rajasthan.

Gajesh Ladhar has also obtained multiple certifications in various fields. These certifications include "Introduction to Machine Learning in Production" from DeepLearning.AI, "A Deep Understanding of Deep Learning" from Udemy, "Tableau 2022 A-Z: Hands-On Tableau Training for Data Science" from SuperDataScience, "Time Series Analysis, Forecasting, and Machine Learning" from Udemy, "Supervised Machine Learning: Regression and Classification" from Stanford Online, "TensorFlow: Advanced Techniques Specialization" from DeepLearning.AI, "Advanced Computer Vision with Tensorflow" from DeepLearning.AI, "Python OOP - Object Oriented Programming for Beginners" from Udemy, "Statistics with Python" from Udemy, "Custom and Distributed Training with TensorFlow" from DeepLearning.AI, "Custom Models, Layers, and Loss Functions with TensorFlow" from DeepLearning.AI, "Interactive Dashboard for AI models using Plotly Dash" from Udemy, "NLP Specialization" from deeplearning.ai, "Data Structure" from UC San Diego, "Natural Language Processing with Sequence Models" from deeplearning.ai, "Algorithmic Toolbox" from UC San Diego, "Convolutional Neural Networks in TensorFlow" from deeplearning.ai, "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" from deeplearning.ai, "Deep Learning Specialization" from deeplearning.ai, and "Natural Language Processing with Classification and Vector Spaces" from deeplearning.ai.