Certificate Program in AI

In the week, you will dive into the world of Artificial Intelligence by straightening out definitions such as AI, ML, DL, RL, 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 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

In the week, you will learn to create and configure a data storage resource on the cloud, 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

In the week, you will learn how to write complex queries for a deeper understanding of data and answering business questions, run quality checks on data through documentation of data profile 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

In the week, 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

In this week, 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

In the 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

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 for transforming raw data into accessible business insights to Key Stakeholders for faster, accurate decision-making.

In the week, you will receive a refresher course on Machine Learning and Deep Learning to strengthen your fundamentals and concurrently, this period will serve as a buffer time for those who might need additional time to finalize your projects

In the week, you will master the skill of pre-processing, training, tuning, and evaluating models for Classification and Regression, learn the systematic procedure of hyper-parameter tuning and experimentation, and comprehend the type of resources and associated costs required for training ML models

Topics Covered: 

• Data Preprocessing for Structured Data
• Model training and how it works for Classification and Regression Models
• Hyper-parameter Tuning 
• Model Performance Evaluation
• Costs associated with Training

In the week, you will carry out pre-processing, training, and evaluating Convolutional Neural Networks (CNNs), learn how to methodically experiment with model parameters, and also understand the type of resources necessary and costs implicated in training Deep Learning models

Topics Covered: 

• Neural Networks Architecture
• Data Preprocessing for Image Data
• Training and Tuning Neural Networks
• Model Performance Evaluation
• Costs associated with Training Deep Learning Models

In the week, 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

In the week, you will master using the Azure OpenAI API to administer prompts on data at scale, be adept at evaluating prompts and responses, and learn to apply various prompt techniques such as Zero-shot, Few-shot, and CoT

Topics Covered:

• Azure OpenAI API - and how to get setup with it on Python
• Prompting Techniques: Zero-shot, Few-shot and CoT
• Evaluating Prompts
• Evaluating LLM Results
• Automating LLM Functions on datasets

In the week, you'll tackle text-based problems like Summarization and Classification, learn to implement Retrieval Augmented Generation (RAG) for Question Answering, and deploy a user-friendly chatbot to cater to a specific use-case

Topics Covered:

• Hugging Face - how to get setup - and how to use it?
• Summarization & Classification and their Evaluation metrics
• What are embeddings and embedding similarity measures - Cosine and Euclidean
• Vector Databases and how they are useful to implement RAG
• Deploying a chat-bot on Azure using App Services

Sample Problem Statement:

ABC Corporation is facing challenges with their customer service. They are struggling due to the inability to process queries in real time. They need a solution which can help them in text-based problem solving, scaling up their data processing, systematically experimenting with Language Models and having an efficient customer interaction through the deployment of a user-friendly chatbot on Azure Cloud, specifically leveraging Azure OpenAI capabilities. This will not only boost their data analytics performance but also enhance customer experience and response time.

In the week, you are expected to pre-read the documentation on how to evaluate and consider costs associated with cloud solutions, as well as gain an overarching view of what an end-to-end Machine Learning Operations (MLOps) solution architecture entails

In the week, you will acquire a basic understanding of version control and its implementation, learn how to effectively set up and utilize Development and Production environments, and learn to operate a simple pipeline while understanding its overall architecture

Topics Covered: 

• Understanding and Implementing Version Control with Git
• Effective Setup and Use of Development & Production Environments
• Running a Simple Pipeline and Understanding its Architecture
• Implementing CICD on Azure
• Managing Projects and Tracking in Azure DevOps

In the week, you will acquire a basic understanding of version control and its implementation, learn how to effectively set up and utilize Development and Production environments, and learn to operate a simple pipeline while understanding its overall architecture

Topics Covered: 

• Understanding and Implementing Version Control with Git
• Effective Setup and Use of Development & Production Environments
• Running a Simple Pipeline and Understanding its Architecture
• Implementing CICD on Azure
• Managing Projects and Tracking in Azure DevOps

Sample Problem Statement:

As Y-Movies continues to expand its data-driven strategies, they are confronted with the challenge of effectively managing machine learning models, from development to deployment. They are experiencing difficulties in automating tasks, maintaining versions, deploying models, and monitoring their performance. This manual and labor-intensive process has been sub-optimal, raising concerns about data quality, potential biases, and our team's capability to focus on strategic insights rather than operational tasks. Therefore, the business problem is to streamline, automate, and enhance our machine learning operations through Azure Cloud to enable efficient model management, robust model monitoring and retraining, and the creation of reliable customer-facing applications. This will eventually improve our decision-making, agility, and overall service of our streaming platform.

Building Data Products - A webinar by an Industry Expert who will give their perspective on how data products are built and integrated today into the products and services we use, and what lies ahead in your learning journey!