Data Analytics & Generative AI Program

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Last Update October 5, 2024

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About This Course

This program helps participants to be proficient in both data analysis and AI. The program includes Advanced Excel, Python, Basic Statistics, SQL & data visualization with Tableau. It also delves into Generative AI technologies such as Hugging Face Transformers, LLMs and DALL-E 2, MidJourney, GANs, RAG, and LangChain to give you a strong foundation in data management and cutting-edge advanced AI tools.

Curriculum

45 Lessons

Introduction to Data Analytics

Introduction to Data Analytics, Why Data Analytics & Importance of Data Analytics00:00

Python

Statistics

Advanced Excel & Data Analysis

SQL

Tableau

Project Session 01

Introduction to Gen AI & Hugging Face Transformers Platform

Language Models and Transformer Models

Large Language Models (LLMs)

LangChain, AI Application Stack and Ethical Considerations

Project Session 02

Your Instructors

skillzrevo

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278 Students

Data Analytics & Generative AI Program

About This Course

Curriculum

Introduction to Data Analytics

Introduction to Data Analytics, Why Data Analytics & Importance of Data Analytics00:00

Python

Introduction to Python, Why Python, Variables, Data Types, Type castings, Strings, Indexing

Operators and Conditional Statements, Looping Statements and it’s Control Statement00:00

Lambda Functions, *args, **kwargs, Functions00:00

Data Structures – List, Tuple and List Comprehensions00:00

Data Structures – Set and Dictionaries00:00

Classes, Objects and Constructors, Inheritance00:00

Polymorphism, Abstraction and Encapsulation00:00

Connecting & Establishing connections to databases, Executing SQL Queries, ORM, Working with NoSQL Databases00:00

Introduction of Numpy, and Pandas00:00

Introduction of Seaborn and Matplotlib00:00

Assignments

Assignments

Statistics

Introduction to Statistics, Descriptive Statistics, Sample, Population, Major of Central Tendency, Standard Deviation00:00

Variance, Range, IQR, Outliers, Correlation, Covariance, Skewness, Kurtosis, Probability00:00

Probability, Probability distributions, Central Limit Theorem, Binomial and Poisson Distribution00:00

Normal Distribution, Type I & Type II Error00:00

T-test, Z-test, Hypothesis, Testing Interview Questions00:00

Assignment

Advanced Excel & Data Analysis

Microsoft Excel Overview, Basic Navigation and Usage, Cell referencing, Formatting Excel, Advanced Formatting, Shortcuts and Basic Formulas00:00

Sorting, Filtering, Advanced Filtering, Charts, Types of Charts, Advanced Charting Techniques and Pivot Tables, Creating, Grouping and Summarizing Data00:00

Lookup Function, Vlookup, Using VLOOKUP with Multiple, Criteria Hlookup, Combining HLOOKUP with Other Functions, Match Function, Using MATCH for Dynamic Referencing00:00

Introduction to VBA & Macros, Understanding VBA basics, Debugging and error handling, Advanced VBA Techniques, Integrating VBA with Excel functions, Designing Effective Dashboards, Building a Dashboard00:00

Understanding the basics of data analysis, Data Import and Cleaning, Using Formulas and Functions, Data Visualization, Descriptive statistics00:00

Advanced Data Analysis Techniques, DAX, Scenario and Sensitivity Analysis, Dashboards and Reports, Case Studies and Real-World Applications, Practical examples of data analysis in Excel00:00

SQL

Basic of Database,Types of Database,Data Types, SQL Operators, Expression, Create, Insert00:00

Drop, Truncate, Delete, Alter, Update, Select, Range, Operator, IN,Wildcard, Like, Clause00:00

Constraint, Aggregation Function, Group by, Order by, Having00:00

Joins, Case, Complex Queries, Doubt Clearing00:00

Quiz 1: Databases and SQL Fundamentals Quiz

Quiz : Core SQL Commands and Data Manipulation .

Assignments

Tableau

Introduction to Tableau, Why Tableau, Tableau Desktop, Tableau products00:00

Data import, Measures, Filters00:00

Data transformation, Marks, Dual Axis00:00

Manage worksheets, Data visualization, Dashboard, Projects00:00

Project Session 01

Data Analytics, Reports & Dashboards00:00

Introduction to Gen AI & Hugging Face Transformers Platform

Intro. to AI, Hype vs. Reality, Business Applications, Ethical Considerations, Intro to Gen AI, From Text Generation to Multi-modal, Potential & Challenges00:00

Intro to Open source Hugging-face Transformers Platform, Review of NLP Basics & Text Pre-processing, Introduction to NLP Concepts: Language Representations, Tokenization, Part-of-Speech Tagging, Text Preprocessing00:00

Feature Engineering: Normalization, Stemming, Lemmatization, Stop Word Removal, Understanding key NLP Applications using Hugging-face platform00:00

Sentiment analysis, Sentence classification, Generating text, Extracting an answer from text00:00

Language Models and Transformer Models

Understanding Language Models, Probability-based Language Models, Unsupervised Learning Language representations, Introduction to Transformer Models, What are Transformer Models00:00

Types of Models: Encoder–Decoder, Decoder only, Attention mechanism, Tasks that Transformer Models can do: translation, text summarization, Q&A, text generation, Zero shot, few shot text classification00:00

Large Language Models (LLMs)

Introduction to Large Language Models (LLMs), – Structure of popular models – Types of Models: text to text, text to image, text to video, Multi-modal00:00

Other types of Generative AI Algorithms, – GANs, VAEs, Diffusion Models, Mixture of Experts, – Different models available currently for image ( DALLE-2, Mid-journey)00:00

Hands on Practice of NLP tasks using Hugging-face library and Opensource Language Models such as Bloom for fine tuning a LLMs, zero and few shot Classification – Applications of Generative AI in business00:00

Customer Insights & Sentiment Analysis, Personalized Marketing & Content Creation, Chat-bots: Automating Customer Service and Support, Document Processing Automation00:00

LangChain, AI Application Stack and Ethical Considerations

LangChain, Applied use case for Gen AI – Hands on Exercise, Designing a custom chat-bot, Data Analytics using Gen AI Model such as Open AI API00:00

AI Application Stack: Infrastructure & Foundation Layer, Overview of AI Infrastructure: Cloud Platforms, GPU, and Distributed Computing, Setting up an AI environment for Generative Models, Infrastructure considerations for scalable AI applications, RAG00:00

Project Session 02

To build practical Applications using cutting-edge NLP techniques with a focus on Generative AI Models and Hugging Face00:00

Your Instructors

skillzrevo

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