Course Overview
Unlock the potential of AI model development with our "Data Science in Action using Ikigailabs" course. This comprehensive program is designed to guide you through the entire process of data science, from problem selection to model deployment, using the versatile Ikigailabs platform.
Course Highlights:
- Practical Methodology: Follow our modified CRISP-DM approach, tailored for big data challenges and validated through large-scale projects.
- Hands-On Experience: Engage in a real-life case study, applying your skills to design and prototype a data science project.
- Clicker Approach: Ideal for beginners, learn to use Ikigailabs, a user-friendly tool, to implement data science solutions without deep coding knowledge.
- Comprehensive 7-Step Process: Master every aspect of data science including:
- Use Case Analysis: Understand and select relevant data science use cases.
- Data Exploration: Dive deep into data sources using Ikigailabs.
- Data Preparation: Get hands-on with dataset preparation.
- Model Development: Apply AI modeling techniques like clustering and regression.
- Model Evaluation: Learn to effectively measure and evaluate your AI models.
- Model Deployment: Understand the processes for deploying AI models.
- Model Monitoring: Master continuous monitoring and evaluation techniques.
This course is perfect for aspiring data scientists, whether you’re a 'clicker' or a 'coder'. For those interested in further exploration, we offer courses in Python coding, advanced machine learning, and AI governance and control.
Start with setting up your Ikigailabs environment and reviewing key data science methodologies. Then, move through each step with detailed instructions, downloadable datasets, and sample codes. Complete assignments in each section and submit your final notebook for a comprehensive learning experience.
Join our "Data Science in Action using Ikigailabs" course to transform your understanding of data science and apply these skills in real-world scenarios.
Expected Outcome
- Understanding Data Science Methodology: Students will learn a proven data science methodology, crucial for navigating the transition from a Business Intelligence (BI) to an Artificial Intelligence (AI) focused approach in dealing with big data challenges.
- Hands-On Case Study Experience: Through a real case study on Health Equity, students will gain practical experience in designing and prototyping a data science project. This hands-on approach ensures a deeper understanding of the process and its application.
- Focus on 'Clickers': The course categorizes data scientists into two groups: 'clickers' and 'coders'. 'Clickers' typically use tools like SPSS Modeler, Excel, and Ikigailabs, which are more GUI-oriented. This course is tailored primarily for 'clickers', providing them with the skills to utilize these tools effectively in data science engagements.
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Ikigailabs as a Teaching Tool: Utilizing Ikigailabs, the course demonstrates all the essential steps and activities required in a data science engagement. Ikigailabs serves as the primary platform for illustrating the practical aspects of data science work, making the learning process more comprehensive and applicable.
Example Curriculum
- Prepare Data - Reduction (6:27)
- Prepare Data - Feature Engineering (7:05)
- Prepare Data - Synthesis (4:14)
- Prepare Data - Data Preparation Toolkits from Ikigailabs (3:29)
- Prepare Data - Task 1: Load Data (8:09)
- Prepare Data - Task 2: Reformat (1:56)
- Prepare Data - Task 3: Filter (6:18)
- Prepare Data - Task 4: Merge (9:54)
- Prepare Data - Task 5: Group (4:37)
- Prepare Data - Task 6: Feature Engineering (5:44)
- Prepare Data - Summary (5:56)
- Quizzes
- Develop Model - Overview (8:35)
- Descriptive Analytics - Simple Statistics (8:02)
- Descriptive Analytics - Bar Chart (5:56)
- Descriptive Analytics - Pie Chart (4:13)
- Descriptive Analytics - Maps (6:00)
- Predictive Analytics - Clustering - Set-up (9:27)
- Predictive Analytics - Clustering - Results (10:02)
- Predictive Analytics - Regression - Set-up (9:31)
- Predictive Analytics - Regression - Results (2:53)
- Prescriptive Analytics - Examples (9:22)
- Prescriptive Analytics - Algorithm (11:58)
- Quizzes
AAII Course Offerings
In our AI series, we have designed many courses on AI related topics such as Vision AI, Conversational AI, Graph AI and Data Science. We are working with a few universities in launching these courses. These courses are aimed as education aid for graduate level courses at leading US universities. We will be releasing these courses on a periodic basis using Teachable as a platform. Please select "View All Products" to view all our courses.
