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Applied Machine Learning for Business Analytics Course

This course is designed to provide learners with a deep understanding of the core principles, techniques, and applications of machine learning in the context of data-driven analytics. The course focuses on equipping students with the knowledge and skills required to develop, implement, and evaluate machine learning models that can be used to solve complex real-world problems in various industries, such as finance, healthcare, marketing, and supply chain management. Learners will explore a range of machine learning algorithms, including supervised and unsupervised learning techniques, reinforcement learning, and deep learning frameworks. They will also learn how to preprocess and analyze data, select appropriate features, and optimize model performance using evaluation metrics and validation strategies. Additionally, the course will cover ethical considerations and best practices in developing and deploying machine learning models.

Next start date: January 1 Start Date
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Course level

Course level

Graduate

Course duration

Course duration

max. 8 weeks

Estimated time per week

Estimated time per week

10-15 hours

Course prerequisites

Course prerequisites

None

Cost

Cost

$ -

Course credits

Course credits

3

Relevant jobs

Relevant jobs

Applied Machine Learning for Business Analytics Course Overview

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Create an analytical solution, integrate its components, and focus on key interoperability points to justify the architectural solution and implementation plan.

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Develop a comprehensive understanding of the cutting-edge technologies that facilitate the creation and advancement of machine learning.

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Determine the appropriate use of the different cloud-based environments using machine learning components such as Azure, Apache Spark, Databricks, Google BigQuery, and OpenAI.

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Explain the process of data cleansing and its importance in data mining and summarize the application areas and industries where data mining is used.

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Identify the appropriate statistical modeling techniques needed to evaluate and resolve a business problem.

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Create a decision-making model based on data by using data mining tools and techniques.

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Evaluate the chosen data mining algorithm, assess modeling accuracy, and analyze the impact on decision-making. Skipping this could lead to poor outcomes.

Applied Machine Learning for Business Analytics Course Skills

Predictive AnalyticsMachine LearningQuantum ML AlgorithmsQEMLForecastingRegression AnalysisClassification

How will I learn?

Your course starts on the first of the month. The course consists of 6 modules, and is designed to take you eight weeks to complete. Nexford’s learning design team has purposefully created courses to equip you with competencies mapped to the skills employers are looking for. Each course has 5-7 learning outcomes based on the skills employers need. Everything you learn gives you measurable skills you will use to succeed in today’s world of work.

Nexford courses are not live or recorded lectures. Instead, they’re reading, videos, interactive elements, quizzes and relevant case studies. Programs include assessments, peer-to-peer discussions, and a final project to practice what you’ve learned in a real-world context. Program content is available 24/7 during the course, and you have opportunities for collaboration and networking with learners during and after your program. Our global community of learners work at top companies such as Microsoft, Deloitte, and Google.

You'll have 24/7 access to success advisors to support you. Faculty also provide you world-class support. Book appointments with them, get individual feedback, and attend regular optional webinars.Nexford courses are rigorous and they encourage critical thinking - because we care about what you know how to do not what you know you have regular hands-on assessments reflecting the business world.

Modules
1: Machine Learning and Relevancy to Predictive Analytics
2: Machine Learning Models
3: Machine Learning Methods
4: Clustering and Dimensionality Reduction
5: Machine Learning Algorithms
6: Quantum Computing and Optimization Algorithms in Machine Learning
7: Final Project

View the catalog to learn about how this course is graded.

You'll get real skills you can use at work, straight away.

Once you've taken one course, you can take more. Using stacked credentials, you’re able to take enough courses to make a certificate, and take enough certificates to build a degree.

If you apply for a Nexford certificate or degree, you'll get credit for each course you take.

What support will I receive?

When you have a dedicated team on your side, you'll never be alone studying at Nexford. Hailing from many different countries and with online education expertise, our faculty provides you world-class support. Ask them questions during one-to-one office hours or live chat, email them any time, and get individual feedback on your assessments.

While you’re learning, you’ll also have full access to the Nexford online library, which includes access to millions of full-text articles, industry reports and key sources such as the Wall Street Journal, the Financial Times and The Economist.

LinkedIn Learning: unlimited access with Nexford

Support your Nexford goals with access to LinkedIn Learning during your program, at no additional cost. Explore the learning hub of the globe’s biggest professional networking platform to:

  • Power your career: choose from over 16,000 expert-led courses, from remote working to data science
  • Show off your skills: earn a certificate when you complete a course
  • See what’s trending: LinkedIn Learning adds 25 new courses each week
  • Tailor your learning: choose relevant courses based on your experience, LinkedIn profile and goals
  • Test what you’ve learned: use LinkedIn Learning assessments