Artificial Intelligence (AI) for All

Seats: 25

Course: 4 Months

Admission: Opened

Overview:

Our Artificial Intelligence course cater both IT and Non-IT professionals, with the primary aim of demystifying the concepts of AI and fostering a comprehensive understanding of its fundamental techniques. Employing innovative teaching methodologies such as case studies, animated examples, and graphics, we ensure an immersive and engaging learning experience for all our students.

This comprehensive course covers an extensive array of topics, tailored to accommodate learners at every proficiency level, ultimately aiming to dispel any apprehensions associated with AI. Topics explored encompass Trends, Technologies, and Tools for AI, AI Applications in Business, Society, and Industry, Problem Solving Strategies, Knowledge-Based Systems, Expert Systems, Natural Language Processing, Robotics, Machine Learning, Neural Networks, Case Studies with Python, and Advanced Topics like Deep Learning, IoT, and AI.

Learning Objectives:

Upon successful completion of this course, participants will:

Acquire a thorough understanding of artificial intelligence and its diverse perspectives.
Explore the myriad roles of AI professionals and its multifaceted applications across various sectors.
Delve into the significance of logic and knowledge-based reasoning in the realm of AI.
Analyze and employ effective problem-solving techniques and game-playing strategies.
Grasp the core principles underlying knowledge-based systems.
Investigate various AI research domains, including Neural Networks, Natural Language Processing, and Robotics.
Gain invaluable insights into the intricacies of the machine learning process and the functioning of machine learning algorithms.
Classify distinct categories of machine learning and become adept at utilizing associated tools.
Demonstrate practical proficiency through hands-on case studies employing Python toolbox.
Enhance Data Analytics skills.
Develop proficiency with large language models (LLMs).
Master Python and its libraries (Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, Scikit-learn) from foundational to advanced levels.
Attain a comprehensive understanding of Microsoft Azure.

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Entry-level Qualifications:

Intermediate or equivalent educational qualification.
Basic understanding of mathematics, including algebra and statistics.
Proficiency in English language comprehension and communication skills.

Required Skills:

Strong analytical skills: Ability to analyze complex problems and break them down into manageable components.
Critical thinking: Capacity to evaluate information objectively and make logical deductions.
Programming proficiency: Basic understanding of programming concepts, preferably in Python.
Familiarity with data handling: Understanding of data structures and basic data manipulation techniques.
Curiosity and eagerness to learn: Willingness to explore new concepts and delve into the intricacies of AI.
Problem-solving abilities: Capacity to approach problems creatively and devise effective solutions.
Attention to detail: Ability to pay close attention to nuances and identify patterns in data.
Collaboration and teamwork: Capability to work effectively in a team environment and collaborate with peers on projects and assignments.
While these qualifications and skills are recommended for entry-level participation in the Artificial Intelligence course, individuals with varying backgrounds and experiences may also benefit from the program. The course structure may accommodate learners with diverse skill sets and provide foundational knowledge to help them succeed in the field of AI.