Data Science & AI Masters 2025 - From Python To Gen AI

Overview

Master Data Science and AI:

Learn Python, EDA, Stats, SQL, Machine Learning, NLP, Deep Learning and Gen AI What you'll learn:

Build a solid foundation in Python programming to effectively implement AI concepts and applications.Learn how Machine Learning & Deep Learning worksLearn how transformer models revolutionize NLP tasks, and how to leverage them for various applications.Gain hands-on experience with Retrieval-Augmented Generation (RAG) and Langchain for building advanced AI applications.Learn how to utilize vector databases for efficient storage and retrieval of embeddings in AI projects.Understand the complete pipeline of Natural Language Processing, from data preprocessing to model deployment.Explore the essentials of Large Language Models (LLMs) and their applications in generative tasks.Develop skills in crafting effective prompts to optimize model performance and achieve desired outputs. Welcome to Data Science & AI Masters 2025 - From Python To Gen AI!

This comprehensive course is designed for aspiring data scientists and AI enthusiasts who want to master the essential skills needed to thrive in the rapidly evolving field of data science and artificial intelligence. Whether you're a beginner or looking to enhance your existing knowledge, this bootcamp will guide you through every step of your learning journey.What You Will LearnIn this bootcamp, you will gain a solid foundation in key concepts and techniques, including:

Python Programming:

Start with the basics of Python, the most popular programming language in data science, and learn how to write efficient code.Exploratory Data Analysis (EDA):

Discover how to analyze and visualize data to uncover insights and patterns.Statistics:

Understand the statistical methods that underpin data analysis and machine learning.SQL:

Learn how to manage and query databases effectively using SQL.Machine Learning:

Dive into the world of machine learning, covering algorithms, model evaluation, and practical applications.Time Series Analysis & Forecasting:

Explore techniques for analyzing time-dependent data and making predictions.Deep Learning:

Get hands-on experience with neural networks and deep learning frameworks.Natural Language Processing (NLP):

Learn how to process and analyze textual data using NLP techniques.Transformers and Generative AI:

Understand the latest advancements in AI, including transformer models and generative AI applications.Real-World Projects:

Apply your skills through engaging projects that simulate real-world data challenges.Course StructureThe bootcamp is structured into modules that build upon each other, ensuring a smooth learning experience.

Each module includes video lectures, hands-on exercises, and quizzes to reinforce your understanding. By the end of the course, you will have a robust portfolio of projects showcasing your skills and knowledge.ConclusionJoin us in The Complete DS/AI Bootcamp and take the first step towards a rewarding career in data science and artificial intelligence.

With the demand for data professionals on the rise, this course will equip you with the skills needed to excel in this exciting field. Enroll now and start your journey to becoming a proficient data scientist and AI expert!

Syllabus

• **Python Programming**
Introduction to Python
Data Structures and Algorithms
Writing Efficient and Clean Code
• **Exploratory Data Analysis (EDA)**
Data Collection and Cleaning
Data Visualization Techniques
Identifying Patterns and Insights
• **Statistics for Data Science**
Descriptive Statistics
Probability Distributions
Hypothesis Testing and Inferential Statistics
• **SQL for Data Management**
Database Design and Management
Writing SQL Queries
Data Manipulation and Aggregation
• **Machine Learning**
Supervised vs. Unsupervised Learning
Model Evaluation and Optimization
Practical Applications and Case Studies
• **Time Series Analysis & Forecasting**
Time Series Data Characteristics
Forecasting Techniques
Seasonal and Trend Analysis
• **Deep Learning**
Introduction to Neural Networks
Training and Optimization Techniques
Using Popular Deep Learning Frameworks
• **Natural Language Processing (NLP)**
Text Preprocessing and Tokenization
Sentiment Analysis and Text Classification
Deployment of NLP Models
• **Transformers and Generative AI**
Overview of Transformer Architecture
Applications in NLP and Beyond
Generative AI Concepts and Use Cases
• **Advanced AI Applications**
Retrieval-Augmented Generation (RAG)
Langchain for Complex AI Solutions
Using Vector Databases for Embedding Management
• **Large Language Models (LLMs)**
Exploration of LLMs in Various Contexts
Effective Prompt Engineering
Customizing LLMs for Specific Tasks
• **Capstone Projects**
Real-World Data Challenges
Hands-On Project Development
Building a Portfolio of AI Solutions

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Taught by

Satyajit Pattnaik and Zep Tech Solutions

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Subjects

Data Science