Get certified in Python for Data Science at Nagpur

Python for Data Analytics is an introductory course designed to teach you the basics of data analytics using the Python programming language. You'll learn how to use Python to explore and analyze datasets, create visualizations, Through hands-on examples and hands-on coding exercises, you'll gain the skills and knowledge you need to become a data analyst. Sign up today and take your data analytics skills to the next level.

Structured Query Programming (SQL) is a course designed to teach you the fundamentals of Structured Query Language (SQL). You'll learn how to write complex queries to extract data from databases, create and modify tables and views, and use basic data manipulation techniques. With the skills you learn in this course, you'll be able to effectively manage, analyze, and present data from a wide variety of sources. Sign up today and get started with SQL.

Microsoft Excel and Power BI is a course designed to help you master the most popular business intelligence tools. You'll learn how to use Excel to manage and analyze data, create powerful visuals, and automate tasks. You'll also learn how to use Power BI to create interactive dashboards and data visualizations. With the skills you learn in this course, you'll be able to quickly and effectively analyze data and make informed decisions. Sign up today and start using Excel and Power BI to your advantage.

This course provides an introduction to the fundamentals of machine learning and data science. Students will learn to apply predictive modeling and machine learning techniques to real-world problems, as well as gaining an understanding of the theoretical underpinnings of these techniques. Topics covered include supervised and unsupervised learning, linear and non-linear models, and more. Students will also gain practical experience with popular machine learning libraries such as scikit-learn. With a focus on hands-on learning, this course is designed to give students the skills they need to become proficient in the field of machine learning and data science.

This course provides students with an introduction to the field of natural language processing (NLP). Students will learn how to apply NLP techniques to text data, as well as gain an understanding of the theoretical underpinnings of these techniques. Topics covered include text preprocessing, part of speech tagging, sentiment analysis, topic modeling, and more. Students will also gain practical experience with popular NLP libraries such as spaCy, NLTK. With a focus on hands-on learning, this course is designed to give students the skills they need to become proficient in the field of natural language processing.

This course provides an introduction to the field of computer vision. Students will learn how to apply computer vision techniques to images and video data, as well as gain an understanding of the theoretical underpinnings of these techniques. Topics covered include image preprocessing, feature extraction, object detection, and more. Students will also gain practical experience with popular computer vision libraries such as OpenCV, scikit-image. With a focus on hands-on learning, this course is designed to give students the skills they need to become proficient in the field of computer vision.