Course Information
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Course Overview
Master Data Science and AI: Learn Python, EDA, Stats, SQL, Machine Learning, NLP, Deep Learning and Gen AI
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 Learn
In 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.
Projects List:
AI Career Coach: A personalized chatbot that guides users in career development and job search strategies using real-time data and insights.
AI Powered Automated Claims Processing: An intelligent system that streamlines insurance claims by automating data extraction and decision-making processes.
Chat Scholar Chatbot + Essay Grading System: An interactive chatbot that assists students with writing and provides AI-driven grading and feedback on essays.
Research RAG Chatbot: A research assistant chatbot that retrieves relevant academic information and generates summaries based on user queries.
Sustainability Chatbot (GROK AI): An eco-focused chatbot that educates users on sustainable practices and provides actionable tips for reducing their carbon footprint.
Multi PDF RAG Chatbot: An intelligent chatbot that utilizes web-scraped data to answer user queries by extracting and summarizing information from multiple PDF documents.
Text to SQL Chatbot (using Gemini): A smart chatbot that converts natural language queries into SQL commands, streamlining data retrieval and analysis for users
If you have a specific project idea in mind, feel free to share it, and we will do our best to bring your vision to life.
Course Structure
The 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.
Conclusion
Join 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!
Course Content
- 19 section(s)
- 519 lecture(s)
- Section 1 Introduction
- Section 2 Python for Data Science
- Section 3 Business Statistics
- Section 4 Exploratory Data Analysis
- Section 5 SQL for Data Science
- Section 6 Machine Learning
- Section 7 Time Series Analysis & Forecasting
- Section 8 Deep Learning & Neural Networks
- Section 9 Natural Language Processing
- Section 10 Transformers & Generative AI
- Section 11 Generative AI (Advanced)
- Section 12 RAG Assessment and Evaluation Metrics
- Section 13 Introduction to Agentic AI
- Section 14 No-Code Tools for Agentic AI
- Section 15 ML/DL Deployment
- Section 16 Data Engineering Basics
- Section 17 Generative AI Projects
- Section 18 Interview Prep (NEW SECTION)
- Section 19 Real-Time Client Discussions (Role Play)
What You’ll Learn
- Build a solid foundation in Python programming to effectively implement AI concepts and applications.
- Learn how Machine Learning & Deep Learning works
- Learn 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.
Skills covered in this course
Reviews
-
MMax Long
Instructor was very knowledgeable and enthusiastic
-
MMukesh Kumar
This course offers comprehensive knowledge about Some Machine learning and deep learning things
-
KKaushik Joshi
My honest Review About this Course I have joined this course expecting that I will be learning something new but the instructor just reading the slides and not explaining well. Also the videos present in this course is available for free on his youtube channel , the instructor even has not putten efforts for making this course just dumped his old videos of youtube. About the coding/projects/practicals part the instructor not even coded the things its written beforehand from public repositories just reading the code ( if we just have to read it why would have taken this course we just read the slides and become ml engineer). Also most of the good reviews about this course are fake/paid reviews . Also the curriculum or the hours this course contains are just fake , you will not understand even a penny from these videos . I request everyone to don't buy this course thinking that it will cover almost everything in ml ( this course is not worth it). I strongly request everyone 🙏 to please don't waste there time and money on this course ( you will better understand from other ml courses).
-
PPrajeesh Kakkarath
Yes, its great match. Just course length gives me kinda goosebumps because it covers depth. At the same time somewhat doubt too. But yeah. Its good.