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Big Data Analytics and Applied Machine Learning with Python Certificate

Big Data Analytics and Applied Machine Learning with Python Certificate

Advance your career in data analytics and applied machine learning in just 10 Saturdays

According to, 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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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


-- OR --

  • 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 Highlights

10 Weeks


Time commitment
80 hours


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

Program Modules

Major components of the program include:

  • Intro to Python
  • Data engineering and DB access with Python
  • Supervised learning
  • Unsupervised learning
  • NLP and text mining
  • Time series analysis
  • Apache Spark
  • Image analysis
  • Data visualization
  • Capstone


The following types of people will benefit from this program:

  • Individuals and college graduates interested in a machine learning career as a data scientist who has already earned a degree in or equivalent practical experience in business, science, engineering, software, and data processing
  • Business intelligence professionals and data analysts who are interested in becoming knowledgeable about the application of machine learning in their field
  • Business leaders who are contemplating the applicability and utility of Machine Learning analytics in their businesses
  • Managers and executives who are interested in becoming effective participants in the selection, implementation, and competent use of machine learning solutions in their businesses