Courses
Difficulty Level: BEGINNER
Age group: 20-39
Tags
Artificial Intelligence - IT Infrastructure Landscape Overview - Revision of Python Programming - Artificial Intelligence and Machine Learning - Advanced Machine Learning - Deep Learning & Neural Networks - Application of Machine Learning in Industries - Capstone Project IT Infrastructure Landscape Overview - Directory Services - Concept of Computer Networking - Cyber Security - Middleware Applications Revision of Python Programming - Knowledge of Python Libraries - Data Structure - Functions - Statistical Functions - Fundamentals of the Linux Operating System Artificial Intelligence and Machine Learning - Introduction to Artificial Intelligence - Logical approach to AI and Knowledge-Based system - Probabilistic approach to AI - Evolutionary Intelligence - Neural Networks & Natural Language Understanding - Introduction to Machine Learning - Learning Deterministic Models Advanced Machine Learning - Machine Learning - Simple linear regression - Multiple regression and Model building - Classification & Classification Algorithms - Clustering Techniques - Information Retrieval Deep Learning & Neural Networks - Fundamentals of Deep Learning - Learning Process and Different Models in Neural Networks - The Math behind Neural Networks - Diving to the Depths of Deep Learning - Convolutional Neural Networks - Recurrent Neural Networks (RNN) - Generative Deep Learning - Advanced Topics in Deep Learning - Tangential Topics of Machine Learning and Neural Networks Application of Machine Learning in Industries - Machines Learning in Banking and Securities - Machine Learning in Communication Media and Entertainment - Machine Learning in Healthcare and Life Science - Machines Learning in Education - Machine Learning in Manufacturing and Petroleum Industries - Applications of Machine Learning in Government Administration - Machine Learning in Insurance Industry - Applications of Machine learning in Retail Industry and Supply Chain - Machine Learning in Transportation and Logistics - Machine Learning in Energy and Utilities Capstone Project - Projects Based on Challenges - Face Detection - Al Chatbot - Restaurant Revenue Prediction - Census Project - Housing Price Prediction
Strong knowledge of mathematics and any programming language
Basic knowledge of statistics and modeling
Conceptual knowledge of Data Science
Practical Implementation: Apply theoretical knowledge by working on hands-on projects that involve building and evaluating simple AI models, thereby reinforcing learning through practical experience.
Data Handling: Gain the ability to collect, preprocess, and analyze data, understanding the importance of data quality and the various techniques for data cleaning and transformation.
Programming Proficiency: Develop skills in programming languages commonly used in AI, with a focus on Python and its libraries like TensorFlow, Keras, and scikit-learn.
Algorithm Familiarity: Learn and understand basic AI algorithms such as decision trees, linear regression, and k-nearest neighbors.
Understanding AI Concepts: Grasp the fundamental concepts and terminology of AI, including machine learning, neural networks, and natural language processing.
Conceptual clarity in IT infrastructure and Python Libraries
Skill in Advanced Machine Learning and Artificial intelligence
Proficiency in Application of Machine Learning in Industries
Deep-insight to data science and neural networks
Mastery in Projects Based on Challenges
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