Cohort-based Course
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Course overview
This course encompasses all the vital elements of data science from Python programming and statistics to machine learning and deep learning, providing a holistic understanding of the field.
It offers hands-on experience with real data sets and useful projects to ensure learners have practical knowledge of different tools and methodologies.
The bootcamp is designed in a way that even individuals without any coding or statistics background can enroll and grasp the complex topics easily.
Guidance from industry professionals enhances the learning experience and provides insights into real-world implementations of data science.
This course can be a significant boost for your professional life. Whether you're looking to pivot into a new career or seeking to upgrade your skills in your current job, this bootcamp has covered every aspect to guide you towards your goal.
01
This module will familiarize students with the basic concepts of data science. It will start with an overview of the field, its applications, and the roles of a data scientist. It will also include an introduction to the tools and technologies used in the industry, including machine learning algorithms and statistical models, data visualization tools, and programming languages like Python and R.
02
This module will enable students to apply the knowledge and skills obtained in the first module. The primary focus will be on data pre-processing, exploratory data analysis, and the use of visualization techniques to understand trends and patterns. Students will learn how to handle different types of data, including structured and unstructured data, and how to use libraries in Python and R for data analysis and visualization.
03
The final module will dive deeper into machine learning methodologies, including both supervised and unsupervised learning techniques. Topics covered will include regression, classification, clustering, association rules, and neural networks. The module will also cover model evaluation metrics and techniques and the concepts of overfitting and regularization. This module will wrap up with a project, where students will apply all the knowledge and skills they gained throughout the course to solve real-world data science problems.
3 modules
Applying knowledge through projects
Exclusive community of fellow members
Access to course materials for a lifetime
Immediate access to the instructor
Feedback and reflection with guidance
Engaging in learning becomes immensely enriching when accompanied by live cohorts, fostering dynamic interactions and shared insights.
The educational experience reaches new heights when learning is undertaken within live cohorts, creating a vibrant and supportive community for knowledge exchange.
Discover the unparalleled benefits of collaborative learning as live cohorts elevate the educational journey, providing real-time engagement and a sense of camaraderie.