Machine Learning, Data Science and Generative AI with Python

Machine Learning, Data Science and Generative AI with Python
Last updated 4/2024
Duration: 18h50m | .MP4 1280×720, 30 fps(r) | AAC, 44100 Hz, 2ch | 7.21 GB

Complete hands-on machine learning and GenAI tutorial with data science, Tensorflow, GPT, OpenAI, and neural networks

What you’ll learn
Implement machine learning at massive scale with Apache Spark’s MLLib
Classify images, data, and sentiments using deep learning
Data Visualization with MatPlotLib and Seaborn
Understand reinforcement learning – and how to build a Pac-Man bot
Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
Use train/test and K-Fold cross validation to choose and tune your models
Build a movie recommender system using item-based and user-based collaborative filtering
Clean your input data to remove outliers
Design and evaluate A/B tests using T-Tests and P-Values

Requirements
You’ll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer. The course will walk you through installing the necessary free software.
Some prior coding or scripting experience is required.
At least high school level math skills will be required.

Description
Discover the Future of Technology with Our Comprehensive Machine Learning & AI Course – Featuring Generative AI, Deep Learning, and Beyond!
Designed for individuals with programming or scripting backgrounds, this course goes beyond the basics, preparing you to stand out in the competitive tech industry. Our curriculum, enriched with over 130 lectures and 18+ hours of video content, is crafted to provide hands-on experience with Python, guiding you from the fundamentals of statistics to the cutting-edge advancements in generative AI.
Why Choose This Course?
Updated Content on Generative AI:
Dive into the latest in AI with modules on transformers, GPT, ChatGPT, the OpenAI API, Retrieval Augmented Generation (RAG), and self-attention based neural networks.
Real-World Application:
Learn through Python code examples based on real-life scenarios, making the abstract concepts of ML and AI tangible and actionable.
Industry-Relevant Skills:
Our curriculum is designed based on the analysis of job listings from top tech firms, ensuring you gain the skills most sought after by employers.
Diverse Topics Covered:
From neural networks, TensorFlow, and Keras to sentiment analysis and image recognition, our course covers a wide range of ML models and techniques, ensuring a well-rounded education.
Accessible Learning:
Course Highlights:
Introduction to Python and basic statistics, setting a strong foundation for your journey in ML and AI.
Deep Learning techniques, including MLPs, CNNs, and RNNs, with practical exercises in TensorFlow and Keras.
Extensive modules on the mechanics of modern generative AI, including transformers and the OpenAI API, with hands-on projects like fine-tuning GPT.
A comprehensive overview of machine learning models beyond GenAI, including SVMs, reinforcement learning, decision trees, and more, ensuring you have a broad understanding of the field.
Practical data science applications, such as data visualization, regression analysis, clustering, and feature engineering, empowering you to tackle real-world data challenges.
A special section on Apache Spark, enabling you to apply these techniques to big data, analyzed on computing clusters.
Transform Your Career Today
Join a community of learners who have successfully transitioned into the tech industry, leveraging the knowledge and skills acquired from our course to excel in corporate and research roles in AI and ML.
Enroll now and embark on a journey that transforms data into powerful insights, paving your way to a rewarding career in AI and ML.
Who this course is for:
Software developers or programmers who want to transition into the lucrative data science and machine learning career path will learn a lot from this course.
Technologists curious about how deep learning really works
Data analysts in the finance or other non-tech industries who want to transition into the tech industry can use this course to learn how to analyze data using code instead of tools. But, you’ll need some prior experience in coding or scripting to be successful.
If you have no prior coding or scripting experience, you should NOT take this course – yet. Go take an introductory Python course first.

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