Machine Learning & Predictive Analytics
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Course
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.
Blended
Mentored
Intermediate
This course is part of a program:
It is not possible to enroll for individual courses on this program. If you wish to take this course, please enroll for the full program.
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.
Course Outline
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
This course is ideal for data professionals, software engineers, and AI/ML enthusiasts looking to build, train, and deploy machine learning models with real-world applications.
Yes, while some coding experience is beneficial, the course provides a structured learning path covering foundational ML concepts before diving into advanced techniques.
By mastering model evaluation, hyperparameter tuning, and predictive analytics, youll gain the skills to build and optimize ML models, making you a strong candidate for AI/ML roles.
This course prepares you for roles such as machine learning engineer, data scientist, predictive analytics specialist, and AI engineer.
The capstone project focuses on building an end-to-end ML model: customer churn prediction, covering data preprocessing, model training, and deployment.
It includes both self-paced content and instructor-led sessions, ensuring structured learning with hands-on guidance.
Yes, you will earn an industry-recognized Certificate of Completion, validating your skills in machine learning and predictive analytics.
Course Offering
Type of certificate
Certificate of Completion
About this course
05 Modules
12 Skills
Includes
Live Instructor-Led Sessions
Hands-On Projects
Quizzes & Labs
Community & Peer Support
Create
End-to-End ML Model: Customer Churn Prediction
Exercises to explore
Training Regression & Classification Models (Scikit-Learn)
Implementing Feature Selection & Dimensionality Reduction (PCA, LDA)
Using SHAP & LIME for AI Explainability
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