In this course, you will develop AI solutions for business problems.
You will:
To ensure your success in this course, you should be familiar with the concepts that are foundational to data science, including:
You can obtain this level of skills and knowledge by taking the CertNexus course Certified Data Science Practitioner (CDSP) (Exam DSP-110).
You must also be comfortable writing code in the Python programming language, including the use of fundamental Python data science libraries like NumPy and pandas. The Logical Operations course Using Data Science Tools in Python® teaches these skills.
Lesson 1: Solving Business Problems Using AI and ML
Lesson 2: Preparing Data
Lesson 3: Training, Evaluating, and Tuning a Machine Learning Model
Lesson 4: Building Linear Regression Models
Lesson 5: Building Forecasting Models
Lesson 6: Building Classification Models Using Logistic Regression and k-Nearest Neighbor
Lesson 7: Building Clustering Models
Lesson 8: Building Decision Trees and Random Forests
Lesson 9: Building Support-Vector Machines
Lesson 10: Building Artificial Neural Networks
Lesson 11: Operationalizing Machine Learning Models
Lesson 12: Maintaining Machine Learning Operations
Appendix A: Mapping Course Content to CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210)
Appendix B: Datasets Used in This Course
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