Learning Paths - Data Science
Python Programming
This course covers a solid foundation in Python programming, emphasizing practical skills essential for software development and data analysis. The curriculum encompasses Python essentials like data structures, object-oriented programming, and libraries such as Numpy and Pandas for data manipulation. Additionally, it delves into web scraping, REST API development, and asynchronous task handling using Celery.
Prerequisites and Eligibility
This course welcomes learners of all educational backgrounds and skill levels. This course is appropriate for beginners and advanced learners, regardless of their level of coding experience.
MACHINE LEARNING
This course provides a comprehensive introduction to data science and machine learning, covering supervised and unsupervised learning techniques including linear regression, decision trees, clustering algorithms, and ensemble methods. Participants learn model selection, evaluation, and optimization strategies, along with essential concepts in probability, statistics, feature engineering, and preprocessing for machine learning tasks.
Prerequisites and Eligibility
This course welcomes learners of all educational backgrounds and skill levels. However, proficiency in Python is a prerequisite, and a basic understanding of mathematics would be an advantage.
DEEP LEARNING
This course provides a comprehensive overview of deep learning, spanning from foundational concepts like neural networks to advanced techniques such as CNNs, RNNs, and GANs. Participants gain practical experience in gradient computation and explore applications like object detection and speech data processing.
Prerequisites and Eligibility
This course welcomes learners of all educational backgrounds and skill levels. However, proficiency in Machine Learning is a prerequisite, and a basic understanding of mathematics would be an advantage.
Natural Language Processing & Recommender systems
This course provides a thorough journey through the fundamentals and applications of Natural Language Processing (NLP), spanning from basic text processing techniques to advanced topic modeling methods. Additionally, it covers the practical insights into content recommendation systems and dimensionality reduction techniques for enhancing the understanding of real-world NLP challenges and solutions.
Prerequisites and Eligibility
This course welcomes learners of all educational backgrounds and skill levels. However, proficiency in Machine Learning is a prerequisite, and a basic understanding of mathematics would be an advantage.
Data Structures and Algorithms
This course progresses from fundamental concepts to more advanced topics in DSA, ensuring a smooth learning curve. Each topic is accompanied by practice problems and exercises to reinforce learning and problem-solving skills.
Prerequisites and Eligibility
This course welcomes learners of all educational backgrounds and skill levels. However, basic understanding of programming and mathematics is a prerequisite.
Dataiku
Dataiku certifications are highly regarded in the data science and analytics industry. This course will cover the fundamental concepts and functionalities of Dataiku DSS and guide you through the process of designing and building end-to-end data pipelines.
Prerequisites and Eligibility
This course welcomes learners of all educational backgrounds and skill levels. However, basic understanding of Data Science is a prerequisite.
Passion Project
We provide opportunities to delve into passion projects with a focus on creating positive social change. Through these projects, learners will not only enhance their technical skills but also gain valuable experience in applying data science methodologies to address real-world social issues.
Prerequisites and Eligibility
For the passion project component, eligibility is limited to students enrolled in the full-time 6-month program, while those enrolled for individual courses are not eligible. This requirement ensures a comprehensive immersion in data science principles and practices, preparing participants to undertake impactful projects.
