Overview:

During this week, you will dive into the world of Artificial Intelligence by straightening out definitions such as AI, ML, DL, RL, and LLM to fully comprehend the scope of this program. Acquaint yourself with an extensive array of problems that can be solved using ML/DL algorithms and frameworks, and learn how an end-to-end AI workflow functions.

Topics Covered:

• Practical Applications and Use cases of AI, ML, DL, RL, and LLMs
• Frameworks: TensorFlow, PyTorch, and Keras for implementing ML/DL models
• Concept of Evaluation Metrics: Accuracy, Precision, Recall, F1-Score, AUROC
• Interpreting Evaluation Metrics for ML Models
• AI Life Cycle and Stages

Week 02: Overview

You will learn to create and configure a data storage resource on the cloud, and grasp how to manage data in a resource, including appending, modifying, deleting, securing, uploading, downloading, renaming, and organizing it into folders, and gain the ability to query data for answering basic business queries effectively.

Topics Covered:

• Overview of database management systems
• Introduction to SQL and its role in data management
• Introduction to DML and DQL in SQL
• Aggregating and organizing data in SQL
• Overview of common in-built functions

Week 03: Overview

Here, you will learn how to write complex queries for a deeper understanding of data and answer business questions, run quality checks on data through documentation of data profiles and conducting business sense checks, and integrate diverse datasets to transform and prepare data for training.

Topics Covered:

• Joins - Inner Join, Left Join, Right Join and Full Join
• Subqueries - Scalar, Row and Table Subqueries
• Set operations - Union, Intersect and Except
• Window Functions
• Custom Functions and Views

Week 04: Overview

You will learn the syntax and semantics of Python including variables, data types, operators, expressions, and statements, harness your skills in functional programming using conditional statements, loops, exceptions, and functions, and acquaint yourself with the various types of compute instances, their pricing, and their usage areas.

Topics Covered:

• Python Variables, Data Types, and Basic Operators
• Functional Programming with Conditional Statements, Loops and Lambda
• Python Data Structures: Lists, Tuples, Sets, and Dictionaries
• Overview Object-Oriented Programming in Python and use cases
• Exploring Python Libraries and Modules for ML/AI

Week 05: Overview

You will develop the ability to extract insights and identify patterns in data using statistics, execute correlation tests to ascertain associations among data sets, and cultivate the skill of coherently presenting insights and recommendations to stakeholders.

Topics Covered:

• Implementing Descriptive Statistics for Univariate Analysis
• Perform Pearson, Spearman, and Kendall Correlation Tests
• Exploring Python's Matplotlib and Seaborn for data visualization
• Best Practices for Effective Visual Storytelling and Presenting Recommendations
• Dimensionality Reduction Techniques: PCA and t-SNE Using Scikit-Learn

Week 06: Overview

In this week, you will acquire the ability to assemble a simple yet effective analytics and reporting workflow, automate report generation, alerts, notifications, and dashboard updates using cloud-based tools, and design a straightforward yet functional data dashboard.

Topics Covered:

• Understanding Business Analytics and Reporting Process
• Azure Alerting and Notification Services
• Creating Interactive Dashboards with Azure Power BI
• Integration of Diverse Data Sources
• Optimizing Reporting Performance and Troubleshooting

Week 07: Overview

Sample Problem Statement: E-comX, an e-commerce firm, is struggling with scattered, unstructured data hampering quick, data-driven decisions. The company requires an Azure-based solution for efficient data storage, with capabilities for complex queries, quality checks, and data integration for training purposes. Leveraging Python and compute resources, the solution should enable pattern recognition, correlation tests, and report automation. Ultimately, a simple, functional dashboard is sought to transform raw data into accessible business insights for key stakeholders for faster, accurate decision-making.

Week 08: Overview

During this week, you will receive a refresher module on Machine Learning and Deep Learning to strengthen your fundamentals. Concurrently, this period will serve as a buffer time for those needing additional time to finalize their projects.

Week 09: Overview

You will get set up with Azure OpenAI Studio, acquire the ability to write effective prompts for unique business use cases, and gain an understanding of how different parameters work and influence the Language Model's responses.

Topics Covered:

• Large Language Models - An Introduction
• How LLMs work - architecture and processes
• Prompt Engineering Fundamentals
• Parameters and Pricing
• Applying PE for point business use cases