Big Data Analytics and Applied Machine Learning with Python Certificate

According to Dice.com, Artificial Intelligence (AI) and machine learning jobs have jumped by almost 75 percent over the past four years. With the global machine learning market expected to reach $209.91 billion by 2029, it's no wonder that machine learning engineers who know their stuff can pull down extraordinary total compensation ranging from $215,000 to as much as $397,000 on an annual basis. Of course, these salaries are for professionals with 3 to 5 years of experience, which shows your potential earning in the future.

This course is a 10-week targeted program that teaches applied skills in developing real-world machine learning (ML) solutions. Through the program, participants will gain hands-on experience in the entire ML spectrum, including data wrangling, visualization, data exploration, algorithm selection, modeling, training, testing, and implementation. Participants will have the opportunity to master in-demand open-source tools in the Python data science ecosystem. After completing the program, participants will have the ability to generate actionable intelligence from diverse datasets (structured, text, web, and time series) for various practical applications. The program is ideal for anyone interested in data science, machine learning, and artificial intelligence-related careers and professionals focused on creating data-enabled solutions utilizing the Python ecosystem. It is an intensive and immersive professional development program. Through an innovative and successful curriculum structure, a novel delivery model, and an outplacement support structure, the program will prepare students for employment in the surging data science and machine learning fields.

The program has two components of core classroom sessions and applied lab sessions. Classroom segments cover the theory and applications of machine learning, along with hands-on learning through in-class projects. The lab sessions leverage the in-class acquired knowledge to build real-world ML models.

Students who complete this program will also be candidates for additional advanced-level programs, such as Emory's Artificial Intelligence-Powered Augmented Data Science.

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LEARNING OUTCOMES

Successful completion of this intensive program will prepare students for careers in machine learning and data science with the following skills:

• Proficiency in leveraging the Python ecosystem for Machine Learning (ML)
• Data engineering and wrangling: Ability to collect, clean, and explore data
• Hands-on experience with NumPy, and Pandas Libraries
• Proficiency in Scikit-Learn for implementing ML algorithms
• Knowledge and skills to build, train, and deploy descriptive and predictive analytics models
• Ability to optimize the performance of ML models through evaluation and selection techniques
• Ability to work with Matplotlib and Seaborn for data visualization and storytelling
• Ability to do text mining using Natural Language Processing tool kits such as NLTK
• Basic knowledge of image processing and analysis
• Familiarity with the use of Spark for data science
• Implementation of real-world ML projects through capstone assignments

PREREQUISITES

• Emory Continuing Education's Business Intelligence certificate

• Equivalent practical experience in the following fields: business, supply chain, healthcare, pharma, science, engineering, statistics, mathematics, IT, and analytics.
• Experience working on advanced excel, database management, statistics, data analysis, and market research would be beneficial but not required.
• Experience in one or more programming languages is helpful but not required.

CERTIFICATE REQUIREMENTS

To receive the certificate, students must:

1. Attend at least 90% of class sessions
2. Complete the capstone project and the final exam with an average score of 75% or higher