Typical admitted student: A bachelor's degree in computer science, engineering, mathematics, or a related field with a minimum GPA of 3.0 is required, along with demonstrated programming experience or relevant coursework in data science.

About This Program

This hands-on course provides an overview of AI and machine learning applications to help participants build smart solutions for real-world business challenges.

Career Outcomes

Gain machine learning skills to advance as Machine Learning Engineer in Business AI

1. Machine Learning Engineer
2. AI Data Analyst
3. AI Solutions Developer
4. Data Scientist

What You'll Learn

Implement supervised and unsupervised machine learning models for predictive analytics.
Develop deep learning neural networks for image and sequence data processing.
Apply AI techniques to real-world problems in data analytics and automation.
Utilize Python libraries like TensorFlow and Scikit-Learn for AI model deployment.

Curriculum Highlights

Coursework includes interactive case studies in text understanding, computer vision, and data mining, with a focus on data preparation, model selection, and testing.

Top Employers

Top employers include tech companies like Google, Amazon, Microsoft, and IBM, as well as consulting firms and industry leaders in data-driven sectors.

Admissions

A bachelor's degree in computer science, engineering, mathematics, or a related field with a minimum GPA of 3.0 is required, along with demonstrated programming experience or relevant coursework in data science.

Application Materials

Statement of Purpose: Required
Letters of Recommendation: 2
Resume: Required
Transcripts: Official transcripts required

Academic Requirements

Degree Required: Bachelor's degree
GRE/GMAT: Not Required
TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)

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