We got the course J Keitsu & AJ Jomah – DSA Mentorship Package
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Created by: J Keitsu & AJ Jomah
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J Keitsu & AJ Jomah – DSA Mentorship Package course is intended to help students understand the basics of Data Science and Artificial Intelligence (AI). It provides an overview of the key concepts and techniques used in data science, covering topics such as data exploration, data analysis, machine learning algorithms, predictive analytics, deep learning networks and applications. The course also covers technologies like Apache Spark, Hadoop, and TensorFlow that are essential for processing and analyzing large datasets. In addition, the course gives students a hands-on experience of programming in Python and using various data science tools. The instructors also provide guidance on how to apply the concepts taught in class to real-world problems. Upon completion of this course, students will have a better understanding of how to use data science and AI techniques for problem solving. The course is designed to teach students the fundamental concepts of data science and artificial intelligence, while providing them with practical experience in applying these techniques. This mentorship package will equip the student with the necessary skills to navigate their career path in the field of data science and AI.
The course provides a comprehensive learning environment that combines lectures, hands-on assignments, and simulations to reinforce the concepts that are taught. Students will have access to a wide range of materials, including lecture notes, study guides, example code, and datasets. They’ll also get the opportunity to interact with industry professionals for advice and mentorship. The course includes both theoretical and practical components. It covers topics such as data manipulation, feature engineering techniques, supervised and unsupervised learning algorithms, model evaluation and selection, and data visualization. By the end of the course, students will be able to create effective machine learning models for predictive analysis and use them to solve various data science tasks.