Goals
- Develop a comprehensive understanding of AI fundamentals.
- Master Salesforce Einstein AI capabilities and their applications in CRM.
- Understand and apply ethical AI considerations in real-world scenarios.
- Learn effective data management techniques for AI, including preprocessing, governance, and privacy compliance.
Study Approach
- Pomodoro Technique: Each session lasts 25 minutes, with 5-minute breaks between sessions and a longer 15-30 minute break after every 4 sessions.
- Forgetting Curve Review: Revise each topic on Day 1 (immediate), Day 3, Day 7, and Day 14 to solidify knowledge retention.
- Active Learning Tasks: Include problem-solving, case study analysis, and hands-on exercises.
4-Week Detailed Study Plan
Week 1: AI Fundamentals
Goal: Understand the basic principles of AI, including definitions, machine learning, and real-life applications.
Day 1: Introduction to AI (2 sessions)
- Task 1: Learn the definition of AI and how it differs from traditional programming. Write notes with examples.
- Task 2: Understand the distinction between Artificial General Intelligence (AGI) and Narrow AI. Create a comparison chart.
- Review Strategy: Revise notes on Day 3, Day 7, and Day 14.
Day 2: Components of AI (3 sessions)
- Task 1: Study the concepts of models, algorithms, and training data. Write examples (e.g., a spam filter model).
- Task 2: Explore feature extraction and feature selection with specific examples (e.g., identifying features in image datasets).
- Task 3: Solve basic questions identifying components of AI systems.
Day 3: Machine Learning and Deep Learning (3 sessions)
- Task 1: Study the types of machine learning: supervised, unsupervised, and reinforcement learning. Create flashcards for definitions.
- Task 2: Learn the structure of neural networks (input, hidden, output layers) and how weights are adjusted during training.
- Task 3: Watch a Trailhead tutorial video on machine learning concepts.
Day 4: AI Applications in Daily Life (2 sessions)
- Task 1: Explore how AI is used in virtual assistants, recommendation systems, and image recognition.
- Task 2: Write a list of real-world CRM applications for these AI technologies (e.g., product recommendations).
Day 5: Practice and Review (2 sessions)
- Task 1: Review all flashcards created this week.
- Task 2: Take a practice quiz on AI basics from Trailhead or another learning platform.
Day 6: Deep Dive into Weak Areas (2 sessions)
- Task: Revisit challenging topics, such as neural networks or feature selection, and study additional resources for clarity.
Day 7: Rest and Light Review (1 session)
- Task: Skim through notes, flashcards, and quiz mistakes to consolidate knowledge.
Week 2: AI Capabilities in CRM
Goal: Learn about Salesforce Einstein features and their role in CRM tasks.
Day 1: Einstein Discovery (2 sessions)
- Task 1: Study data analysis and insights extraction. Write examples (e.g., predicting customer churn).
- Task 2: Learn how Einstein automates predictive model creation. Watch a Trailhead example.
Day 2: Einstein Vision (3 sessions)
- Task 1: Understand image recognition and its role in retail and manufacturing.
- Task 2: Research a specific use case for Einstein Vision (e.g., inventory tracking) and summarize it.
- Task 3: Practice explaining Einstein Vision capabilities in your own words.
Day 3: Einstein Language (3 sessions)
- Task 1: Study text classification and sentiment analysis with examples (e.g., routing emails based on urgency).
- Task 2: Learn how NLP enhances customer service (e.g., chatbots).
- Task 3: Solve case study questions using Einstein Language scenarios.
Day 4: AI in CRM Customer Management (3 sessions)
- Task 1: Learn how AI personalizes customer journeys (e.g., targeted email campaigns).
- Task 2: Explore lead scoring and prioritization. Write examples of CRM tools that use these techniques.
- Task 3: Map the customer lifecycle stages to Einstein features.
Day 5: Sales Forecasting and Customer Service (2 sessions)
- Task 1: Study how predictive analytics improves sales forecasting with real-world examples.
- Task 2: Learn about intelligent chatbots and automated case routing. Write a short use-case scenario.
Day 6: Practice and Review (3 sessions)
- Task 1: Create flashcards summarizing Einstein features.
- Task 2: Take a Trailhead quiz on Salesforce Einstein.
- Task 3: Write answers to mock questions about AI applications in CRM.
Day 7: Rest and Light Review (1 session)
- Task: Skim notes and flashcards; identify weak areas for follow-up.
Week 3: Ethical Considerations of AI
Goal: Master ethical challenges, Salesforce Trusted AI principles, and decision frameworks.
Day 1: Bias in AI (2 sessions)
- Task 1: Learn the sources of bias and how it impacts AI decisions.
- Task 2: Study how diversified datasets can reduce bias. Write examples.
Day 2: Transparency and Accountability (3 sessions)
- Task 1: Study explainability and the risks of black-box models. Write a case where explainability is crucial (e.g., medical AI).
- Task 2: Learn how to address AI system errors.
- Task 3: Write a list of accountability best practices for AI.
Day 3: Privacy and Security (3 sessions)
- Task 1: Study GDPR and CCPA requirements. Write down key points.
- Task 2: Explore Salesforce’s commitment to data privacy.
- Task 3: Learn about technical measures like encryption and access control.
Day 4: Salesforce Trusted AI Principles (3 sessions)
- Task 1: Learn Salesforce’s principles of fairness, trustworthiness, and privacy.
- Task 2: Map these principles to ethical use cases.
- Task 3: Write a summary of how Salesforce ensures ethical AI.
Day 5: Ethical Decision Framework (2 sessions)
- Task 1: Study how to balance AI performance with ethical considerations.
- Task 2: Write potential business scenarios and analyze them ethically.
Day 6: Practice and Review (3 sessions)
- Task 1: Create flashcards for ethical challenges and solutions.
- Task 2: Take Trailhead quizzes on ethics.
- Task 3: Write out answers to case study questions.
Day 7: Rest and Light Review (1 session)
- Task: Consolidate notes, revise flashcards.
Week 4: Data for AI
Goal: Learn data preprocessing, governance, and optimization techniques.
Day 1: Data Quality and Cleaning (2 sessions)
- Task 1: Study how noise, incomplete data, and redundancy affect performance.
- Task 2: Learn data cleaning and standardization techniques.
Day 2: Data Preprocessing (3 sessions)
- Task 1: Study handling missing values and deduplication.
- Task 2: Learn normalization and scaling with examples.
- Task 3: Practice preprocessing tasks using sample datasets.
Day 3: Privacy and Compliance (3 sessions)
- Task 1: Revisit GDPR, CCPA, and Salesforce privacy measures.
- Task 2: Explore data encryption techniques.
- Task 3: Write compliance scenarios for AI projects.
Day 4: Data Governance (2 sessions)
- Task 1: Study the data lifecycle and governance practices.
- Task 2: Write a plan for managing AI-related data in a business.
Day 5: Data Optimization (3 sessions)
- Task 1: Study data augmentation techniques.
- Task 2: Learn sampling methods (under-sampling and over-sampling).
- Task 3: Explore feature selection and engineering.
Day 6: Final Review and Mock Exam (3 sessions)
- Task 1: Take a full-length mock exam.
- Task 2: Review mistakes and weak areas.
- Task 3: Revise notes and flashcards.
Day 7: Rest and Final Review (1 session)
- Task: Skim all topics and ensure clarity on challenging areas.
By following this structured plan, with targeted tasks, review schedules, and active learning methods, you’ll maximize understanding and retention for the Salesforce AI Associate Certification. Good luck!