Machine Learning & Predictive Analytics

Enrollment is Closed

Overview

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Enrollment is Closed
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Course

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Machine Learning & Predictive Analytics

Master machine learning and predictive analytics! Learn regression, classification, and advanced modeling to solve real-world problems and create impactful AI solutions.

Online Live Classes

Mentored

Intermediate

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Starts on

Jun 21, 2025

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Duration

6 weeks
8 Hours/Week
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Fee

$1,499

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Enrollment is Closed

Machine learning is transforming industries by enabling data-driven decision-making. This course focuses on practical skills for building, training, and deploying ML models, equipping you to solve real-world problems with predictive analytics.

In this course, you will explore essential techniques, including regression, classification, clustering, and ensemble learning, using Python and scikit-learn. Plus, youll gain hands-on experience in feature engineering, model evaluation, hyperparameter tuning, and optimizing models for accuracy and interpretability.

By the end of this course, you will be prepared to apply predictive analytics to real-world challenges in business, healthcare, and finance. You will also be equipped to build scalable, reliable AI solutions that drive meaningful impact.

This course comprises 5 purposely designed modules that take you on a carefully defined learning journey.

Our proven learning methodology blends the best that instructor-led training and self-paced learning have to offer. Leveraging the power of instructor feedback, mentor-supported hands-on practice, and additional home-based studying, you will build the deep technical and practical understanding todays employers are looking for.

Additionally, you will enjoy learning via an interactive online classroom environment where you will be able to participate and actively engage with your peers, instructors, and mentors. Plus, you will get the opportunity to earn recognized certifications which will help your resume and LinkedIn profile stand out.

The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs, and online exam questions.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.

Once you have successfully completed the course, you will earn your Certificate of Completion.

By the end of this course, you will have:

  • Trained and evaluated supervised and unsupervised ML models.
  • Developed model interpretability skills using SHAP and LIME.
  • Gained expertise in identifying and addressing AI model hallucinations.
  • Automated ML pipelines for seamless deployment.

  • Software engineers & developers Integrating AI into software solutions.
  • Data analysts & BI professionals Expanding AI-driven data processing & modeling.
  • Data engineers Utilizing AI for data transformations & model deployment.
  • IT professionals & system administrators Exploring AI & MLOps applications.
  • Product managers & tech consultants Managing AI product development & strategy.
  • Aspiring AI/ML engineers Transitioning into AI & machine learning roles.

  • Basic Python programming Familiarity with Python syntax, functions, and data structures is recommended.
  • Fundamental math & statistics Understanding of basic algebra, probability, and statistical concepts is helpful.
  • Basic knowledge of data handling Experience with Pandas, NumPy, or SQL for data manipulation is beneficial but not required.
  • No prior machine learning experience required The course covers ML concepts from the ground up.