About the Course
Overview: The AI/ML Engineer program at ZICT is a comprehensive training course designed to equip participants with the knowledge and practical skills needed to excel in artificial intelligence (AI) and machine learning (ML) engineering roles. The program covers foundational concepts, advanced techniques, practical applications, and career development aspects to prepare participants for success in the rapidly evolving field of AI and ML.
Target Audience: This program is ideal for:
IT Professionals looking to transition into AI and ML engineering roles.
Recent Graduates or Students interested in pursuing a career in AI and ML.
Data Analysts or Data Scientists seeking to enhance their skills in machine learning and AI technologies.
Software Developers eager to delve into AI and ML application development.
Professionals and Business Owners aiming to leverage AI/ML for innovative solutions in their fields.
Anyone Passionate About AI and MLÂ who wants to break into the industry or advance their career.
Salary Expectation: The salary expectation for AI/ML engineers can vary based on factors such as experience, location, industry, and specific skills. Generally, AI/ML engineers can expect competitive salaries, with entry-level positions starting around $70,000 to $100,000 annually, and experienced professionals earning well over $150,000 per year, particularly in high-demand regions or industries.
Demand: The demand for AI/ML engineers is consistently high across various industries, including technology, healthcare, finance, e-commerce, and more. As organizations increasingly adopt AI and ML technologies to drive innovation, improve decision-making, and enhance customer experiences, the need for skilled AI/ML engineers continues to grow. This demand is expected to remain strong in the coming years, offering abundant opportunities for qualified professionals.
Curriculum Outline (15 Weeks)
Introduction to AI and ML Engineering (1 week) – Overview of AI/ML concepts and tools setup.
Foundations of Machine Learning (3 weeks) – Core algorithms and hands-on practice with ML techniques.
Deep Learning and Neural Networks (3 weeks) – Neural architectures, training methods, and frameworks like TensorFlow.
Natural Language Processing (NLP) (2 weeks) – Text processing, sentiment analysis, and NLP applications.
Advanced Topics in AI/ML Engineering (2 weeks) – Specializing in reinforcement learning, computer vision, and AI ethics.
Capstone Project and Practical Applications (2 weeks) – Real-world project development and deployment.
Career Development and Soft Skills (2 weeks) – Resume building, interview prep, and professional communication.