Explore the world of Generative AI with our comprehensive Mastering Generative AI Course. Designed to provide in-depth knowledge and practical experience, this course covers foundational concepts like neural networks, deep learning applications, and generative adversarial networks (GANs).
We crafted Mastering Generative AI Course an extensive and ambitious curriculum that spans from Python fundamentals to advanced topics like Generative AI and Large Language Models. It’s clear that you’re aiming to provide a thorough education in data science and machine learning. However, I notice there are some areas where the structure could be optimized to enhance the learning experience.
Engage in practical projects such as breast cancer prediction, flight fare prediction, and leaf disease detection using Pytorch. By participating, you will gain proficiency in tools like Pytorch, NumPy, Pandas, Sklearn, and Matplotlib. Additionally, the course helps you develop skills in deep learning, computer vision, and generative AI techniques through the Mastering Generative AI Course.
We'll help you find the right opportunities and connect with employers.
Stay up-to-date with industry trends and best practices.
Get expert help with resume building and mock interviews to ace your applications.
Earn ₹1499 upon project completion and LinkedIn post!
Build a portfolio of real-world projects to impress potential employers.
Showcase your skills and network with pros (worth ₹1499)!
Boost your profile and get noticed by recruiters.
Enroll Today! Join the Mastering Generative AI Course and take your first step towards mastering Generative AI. Limited seats available, so don’t miss out!
6 -33 comprehensive modules Practical projects and hands-on experience Real-world applications and case studies Interactive elements like quizzes and assignments
Breast Cancer Prediction with ANN Pytorch
Flight Fare Prediction with ANN Pytorch
Leaf Disease Detection using CNN Pytorch
MNIST Digits Generation with Simple GAN
Predicting Sales for FMCG Products
Pytorch: Deep learning framework
NumPy & Pandas: Data manipulation
Sklearn: Machine learning models
TorchVision: Image data handling
Matplotlib & Seaborn: visualization
TensorBoard: Monitoring training
Jupyter Notebook: Interactive coding
Deep Learning Fundamentals
Pytorch Proficiency
Computer Vision Basics
Generative AI Techniques
Machine Learning Expertise
Data Preprocessing
Model Evaluation
Python Programming
After completing the course, participants will receive a certificate that showcases their expertise in generative AI and deep learning. This certification aims to boost your career prospects in this rapidly evolving field.
Unlock the Future of AI with Our Mastering Generative AI Course
Join Pantech eLearning’s industry-leading Generative AI course designed to transform you into a skilled AI developer. Whether you’re a beginner or a professional, this program covers generative adversarial networks (GANs), variational autoencoders (VAEs), Transformer models, and cutting-edge tools like TensorFlow, PyTorch, ChatGPT, and DALL-E.
Day 1: Introduction & Setup
Getting started with Python installation.
Setting up the development environment.
Day 2: Python Basics
Variables, data types, and basic operations.
Control flow statements and loops.
Day 3: Python Data Structures
Lists, tuples, dictionaries, and sets.
Practical exercises on data manipulation.
Day 4: Programming Fundamentals
Functions and modules.
Error handling and debugging.
Day 5: Classes and Objects
Object-oriented programming concepts.
Building reusable code with classes.
Day 6: Pandas Library
DataFrames, series, and basic methods.
Importing/exporting data from various formats.
Day 7: Project 1 – Sales Data Analysis
Utilizing Pandas for real-world data analysis.
Drawing insights from sales datasets.
Day 8: Working with NumPy Arrays
Understanding arrays and matrices.
Mathematical operations with NumPy.
Day 9: Data Visualization with Matplotlib and Seaborn
Creating aesthetically pleasing plots.
Customizing graphs for better storytelling.
Day 10: Project 2 – World Population EDA
Exploratory Data Analysis on global datasets.
Visualizing trends and patterns.
Day 11: Introduction to Scikit-Learn
Overview of the library and its applications.
Data preprocessing techniques.
Day 12: Handling Null Values and Outliers
Imputation methods.
Detecting and treating outliers.
Day 13: Feature Scaling and Encoding
Normalization and standardization.
Encoding categorical variables.
Day 14: Machine Learning Algorithms – Part I
Linear models: Linear and Logistic Regression.
Model training and evaluation.
Day 15: Machine Learning Algorithms – Part II
SVM, Decision Trees.
Understanding model complexities.
Day 16: Advanced Algorithms
Ensemble methods: Random Forest, Gradient Boosting.
Naive Bayes, K-Nearest Neighbors.
Day 17: Hyperparameter Tuning & Model Evaluation
Grid Search, Random Search.
Cross-validation techniques.
Day 18: Project 3 – Credit Card Fraud Detection
Building a classification model.
Dealing with imbalanced datasets.
Day 19: Project 4 – Calories Burnt Prediction
Regression analysis.
Model optimization strategies.
Day 20: Project 5 – Music Dataset Clustering & PCA
Unsupervised learning concepts.
Dimensionality reduction techniques.
Day 21: NLP Basics
Text preprocessing techniques.
Introduction to Natural Language Processing.
Day 22: Working with Text Data
Regular Expressions (REGEX).
Tokenization, stemming, lemmatization.
Day 23: Advanced Text Preprocessing
Part-of-Speech tagging.
Named Entity Recognition.
Day 24: Project 6 – Amazon Sentiment Classification
Building a sentiment analysis model.
Handling large datasets.
Day 25: Deep Learning Introduction
Neural networks fundamentals.
Activation functions and layers.
Day 26: Word Embeddings Theory
Understanding word vectors.
Implementing Word2Vec and GloVe.
Day 27: Advanced Preprocessing Techniques
Handling sarcasm, context, and ambiguity.
Text augmentation strategies.
Day 28: RNN and LSTM Architectures
Sequence modeling.
Dealing with time-series data.
Day 29: Project 7 – Next Word Prediction
Building predictive text models.
Evaluating sequence models.
Day 30: Project 8 – Poem Generation
Creative applications of RNNs and LSTMs.
Fine-tuning for stylistic outputs.
Day 31: Introduction to Generative AI
Overview of generative models.
Applications in various industries.
Day 32: PyTorch Basics
Tensors and dynamic computation graphs.
Building models with PyTorch.
Day 33: Deep Learning Concepts
Optimizers and loss functions.
Backpropagation and weight updates.
Day 34: Creating Neural Networks with PyTorch
Implementing custom architectures.
Debugging and visualization tools.
Day 35: Project 9 – Breast Cancer Prediction with ANN
Applying neural networks to healthcare data.
Interpreting model outputs.
Day 36: Computer Vision Basics
Image processing fundamentals.
Convolution operations.
Day 37: TorchVision Library
Preprocessing image data.
Using pretrained models.
Day 38: Convolutional Neural Networks (CNN)
Deep dive into CNN architectures.
Feature extraction from images.
Day 39: Project 10 – Leaf Disease Detection with CNN
End-to-end image classification.
Deployment considerations.
Day 40: GANs Basics
Understanding Generative Adversarial Networks.
Training GANs effectively.
Day 41: Project 11 – MNIST Digit Generation with GAN
Hands-on GAN implementation.
Evaluating generative models.
Day 42: Advanced Generative Models
Variational Autoencoders.
Conditional GANs.
Day 43: Implementing Autoencoders
Data compression techniques.
Anomaly detection applications.
Day 44: Image Generation with GANs
Style transfer.
Super-resolution imaging.
Day 45: Advanced Computer Vision Techniques
Object detection and segmentation.
Use cases in self-driving cars.
Day 46: Transfer Learning for Image Classification
Leveraging pretrained models.
Fine-tuning techniques.
Day 47: Deep Learning Optimizers and Loss Functions
Exploring Adam, RMSprop, etc.
Custom loss functions for specific tasks.
Day 48: Project 12 – Advanced GAN Application
Creative project of choice.
Pushing the boundaries of GANs.
Day 49: Transformers Architecture
Revolutionizing NLP with Transformers.
Self-attention mechanism.
Day 50: Fine-Tuning Pretrained LLMs
Working with LLAMA2 and Google Gemini.
Customizing models for specific use-cases.
Day 51: Project 13 –
Chat with Any PDF using LLAMA2
Building intelligent document assistants.
Parsing and understanding text.
Day 52: Project 14 – Blog Generation with LLM
Automating content creation.
Ethical considerations.
Day 53: Project 15 – SQL Query Generation with Google Gemini
Bridging AI and databases.
Enhancing data accessibility.
Day 54: Project 16 – YouTube Video Summarizer App
Processing multimedia content.
Summarization techniques.
Day 55: SEQ to SEQ Models
Sequence-to-sequence learning.
Applications in translation and summarization.
Day 56: Text Summarizer Project
Building models to condense information.
Evaluating summarization quality.
Day 57: Deployment Strategies
Serving models in production.
API development and microservices.
Day 58: Ethics in AI
Responsible AI practices.
Bias mitigation strategies.
Day 59: Career Guidance
Building a portfolio.
Interview preparation.
Day 60: Final Capstone Project Presentation
Showcasing your work.
Feedback and next steps.
Delve into the world of Generative AI and deep learning with Pytorch. From foundational concepts to real-world applications, Mastering Generative AI Course covers
Understand the basics and build neural networks using Pytorch.
Explore Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN).
Learn model evaluation, hyperparameter tuning, and handling common issues like missing data and outliers.
Engage in practical projects like Breast Cancer Prediction, Flight Fare Prediction, and Leaf Disease Detection.
__________________
Domain: Retail Analytics, Business Intelligence
Technology: Python, Pandas
Trend: Data Analysis, Big Data Handling
Career Relevance: Data Analyst, Business Analyst
Domain: Demographics, Social Research
Technology: Python, Pandas, Matplotlib, Seaborn
Trend: Data Visualization, Statistical Analysis
Career Relevance: Data Analyst, Research Scientist
Domain: Finance, Cybersecurity
Technology: Python, Scikit-Learn, Machine Learning Algorithms
Trend: Fraud Detection using Machine Learning
Career Relevance: Data Scientist, Fraud Analyst, Security Analyst
Domain: Finance, Cybersecurity
Technology: Python, Scikit-Learn, Machine Learning Algorithms
Trend: Fraud Detection using Machine Learning
Career Relevance: Data Scientist, Fraud Analyst, Security Analyst
Domain: Entertainment, Music Industry Analytics
Technology: Python, Unsupervised Learning, PCA, Clustering Algorithms
Trend: Recommender Systems, Big Data in Entertainment
Career Relevance: Machine Learning Engineer, Data Analyst in Media
Domain: E-commerce, Customer Insight
Technology: Python, Natural Language Processing (NLP), Text Classification
Trend: Sentiment Analysis on User Reviews
Career Relevance: NLP Engineer, Data Scientist, Market Analyst
Domain: Language Modeling, AI Assistants
Technology: Python, Deep Learning, Recurrent Neural Networks (RNN), LSTM
Trend: Predictive Text Technologies
Career Relevance: NLP Specialist, AI Developer
Domain: Creative AI, Literature
Technology: Python, Deep Learning, RNN, LSTM
Trend: Generative Models in Creative Arts
Career Relevance: AI Researcher, Creative Technologist
Domain: Medical Diagnostics, Healthcare
Technology: Python, PyTorch, Artificial Neural Networks (ANN)
Trend: Deep Learning in Medical Imaging
Career Relevance: Data Scientist in Healthcare, AI Specialist
Domain: Agriculture Technology, Environmental Science
Technology: Python, PyTorch, Convolutional Neural Networks (CNN)
Trend: Computer Vision in Agriculture, AI for Sustainability
Career Relevance: Computer Vision Engineer, Agricultural Data Scientist
Domain: Computer Vision, Image Processing
Technology: Python, PyTorch, Generative Adversarial Networks (GAN)
Trend: Generative AI, Image Synthesis
Career Relevance: AI Engineer, Research Scientist
Domain: Varies (e.g., Fashion, Art, Gaming)
Technology: Python, PyTorch, Advanced GAN Techniques
Trend: Innovative Uses of Generative AI
Career Relevance: AI Researcher, Deep Learning Specialist
Domain: Document Processing, AI Assistants
Technology: Python, LLAMA2, Large Language Models (LLMs)
Trend: Intelligent Document Interaction
Career Relevance: NLP Engineer, AI Developer
Domain: Content Creation, Digital Marketing
Technology: Python, LLMs, Natural Language Generation
Trend: Automated Content Generation
Career Relevance: AI Content Strategist, NLP Developer
Domain: Database Management, AI Automation
Technology: Python, Google Gemini, NLP
Trend: AI-Assisted Programming, Low-Code Platforms
Career Relevance: Data Engineer, AI Programmer
Domain: Media Technology, Video Content Analysis
Technology: Python, Google Gemini, LLMs, NLP
Trend: Content Summarization, AI in Media
Career Relevance: AI Developer, Data Scientist in Media
Curious about how to get started or which path suits you best? Let’s delve deeper into your interests and craft a personalized learning journey that aligns with your career goals in Mastering Generative AI Course.
From basics to advanced topics.
Learn from expert in AI field
Apply what you learn to real-world problems.
GitHub is a fantastic way to showcase your projects and skills.
Preparing for mock interviews is a fantastic way to build confidence and ensure you’re ready for the real thing.
let’s get you set up with some tailored guidance to help you land that dream job in the tech field.
AI/ML Enthusiasts eager to specialize in generative AI.
Developers & Data Scientists aiming to upskill.
Students preparing for AI careers.
Tech Professionals seeking innovation in healthcare, gaming, or finance.
Graduates can pursue roles like:
Generative AI Developer
Machine Learning Engineer
AI Research Scientist
Data Analyst (AI Specialization)
Self-Paced Learning: Access 24/7 course materials, video lectures, and code repositories.
Community & Mentorship: Join forums and live Q&A sessions.
Affordable Pricing: Premium training with lifetime access.
Curious where our graduates make their mark? Our students go on to excel in leading tech companies, innovative startups, and prestigious research institutions. Their advanced skills and hands-on experience make them highly sought-after professionals in the industry.
EXCELLENT Based on 5972 reviews Swetha Senthil2024-09-18Trustindex verifies that the original source of the review is Google. I completed my python internship guidance of mentor poongodi mam. She thought us in friendly qay Durga Bala2024-09-18Trustindex verifies that the original source of the review is Google. Poongodi mam done very well She took the class very well When we ask any doubt without getting bored she will explain,we learned so much from mam,marvelous Subharanjani2024-09-18Trustindex verifies that the original source of the review is Google. I recently completed Python internship under the guidance of poongodi mam who excelled in explaining concepts in an easily understandable way S Pushpanandhini2024-09-18Trustindex verifies that the original source of the review is Google. Fantastic class we were attended..we got nice experience from this class..thank you for teaching python mam... ANTON'S CREATIONS ___ Anton Rosario Xavier2024-09-17Trustindex verifies that the original source of the review is Google. The learning experience was really worth since more than gaining just the knowledge all of the inputs were given in a friendly and sportive manner which then made it a good place to learn something with a free mindset... 👍🏻 Achu Achu2024-09-16Trustindex verifies that the original source of the review is Google. I recently completed my full stack python intership under the guidance of mentor Gowtham,who excelled in explaining concepts in an easily understand manner Nandhini Baskar2024-09-16Trustindex verifies that the original source of the review is Google. Gowtham-very interesting class and I learning so many things in full stack python development and I complete my internship in Pantech e learning and it is useful for my career
The course includes:
Job Assistance: Guidance in finding the right job opportunities and connections with employers.
Weekly Live Sessions: Stay updated with industry trends and best practices.
HR Support: Expert help with resume building and mock interviews.
Cash Back: Earn ₹1499 upon project completion and posting your project on LinkedIn.
Capstone Projects: Build a portfolio of real-world projects.
Free Hackathon Entry: Participate in hackathons worth ₹1499 and showcase your skills.
LinkedIn Endorsement: Boost your profile and get noticed by recruiters.
Our team helps you identify suitable job openings, refine your applications, and prepare for interviews. We leverage our industry connections to recommend you to potential employers.
The weekly live sessions cover current industry trends, technical skills, best practices, and provide an opportunity for Q&A with industry experts.
You can earn the cashback by completing your course projects and sharing them on LinkedIn, showcasing your work to potential employers and peers.
The HR support includes personalized resume reviews, mock interviews to build your confidence, and tips on improving your interview performance.
Capstone projects are comprehensive assignments that simulate real-world challenges. Completing these projects helps you build a strong portfolio that demonstrates your practical skills to employers.
Participating in hackathons allows you to apply your skills in a competitive environment, collaborate with peers, and network with industry professionals. Winning or performing well in hackathons can also be a valuable addition to your resume.
A LinkedIn endorsement from our course enhances your profile’s credibility and visibility. It shows recruiters that you have been recognized for your skills by a professional training program.
You can enroll by visiting our course page, selecting the limited time offer, and completing the registration process. Payment can be made online through secure gateways.
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