Top 10 Artificial Intelligence Courses to Learn in December 2024
Looking to enhance your skills? We’ve curated a list of the top-rated artificial intelligence courses available this month. These courses are highly rated by students and offer comprehensive learning experiences.
10. AI-Videos: Be a Filmmaker with Artificial Intelligence
Instructor: Arnold Oberleiter
Text to Video: SORA by OpenAI, Heygen, RunwayML, Pika, Stable Diffusion, Dream Machine and Google Colab for social media
Course Highlights:
- Rating: 4.67 ⭐ (217 reviews)
- Students Enrolled: 2175
- Course Length: 23314 hours
- Number of Lectures: 57
- Number of Quizzes: 0
AI-Videos: Be a Filmmaker with Artificial Intelligence, has an average rating of 4.67, with 57 lectures, based on 217 reviews, and has 2175 subscribers.
You will learn about Fundamentals of AI Videos Prompt Engineering for AI Videos and everything about Diffusion Models, Loras, Seeds, and Checkpoints An overview of SORA by OpenAI Everything about Stable Video Diffusion: The simplest tool for AI videos from images MoonvalleyAI: Free Text-to-Video tool on Discord RunwayML: Everything you need to know PikaLabs: Text to Video, Video to Video, Image to Video, and Video Editing Haiper AI: Powered by Google Deepmind All about PixVerse, Morph Studios, and LTX Studios, Kaiber InVideo, Fliki, Kaiber, Lalamu, and more All about AI Avatars like Heygen, D-ID, Synthesia, Elai, and more AI videos and avatars for SEO, onboarding, social media marketing, customer acquisition, explainer videos, branding, and more Introduction to Google Colab and the best tools like Wrapfusion, Deforum, Wav2Lip, Faceswap, Deepfake, and more Personal projects such as creating, editing & cutting videos with CapCut, Pika, Shotcut Pictory and WOXO for the very lazy: Complete videos with one click Opus Pro for YouTube Shorts, Instagram, or TikTok Insight into Canva and Adobe Express for Instagram Reels and more The future of AI videos for the job market Copyrights, data protection, and copyright This course is ideal for individuals who are This course is designed for anyone interested in using AI tools for video creation, regardless of their background. or For individuals who are curious about AI and want to learn about AI videos or For entrepreneurs who want to become more efficient and save money or For anyone who wants to learn something new It is particularly useful for This course is designed for anyone interested in using AI tools for video creation, regardless of their background. or For individuals who are curious about AI and want to learn about AI videos or For entrepreneurs who want to become more efficient and save money or For anyone who wants to learn something new.
Learn More About AI-Videos: Be a Filmmaker with Artificial Intelligence
What You Will Learn
- Fundamentals of AI Videos
- Prompt Engineering for AI Videos and everything about Diffusion Models, Loras, Seeds, and Checkpoints
- An overview of SORA by OpenAI
- Everything about Stable Video Diffusion: The simplest tool for AI videos from images
- MoonvalleyAI: Free Text-to-Video tool on Discord
- RunwayML: Everything you need to know
- PikaLabs: Text to Video, Video to Video, Image to Video, and Video Editing
- Haiper AI: Powered by Google Deepmind
- All about PixVerse, Morph Studios, and LTX Studios, Kaiber InVideo, Fliki, Kaiber, Lalamu, and more
- All about AI Avatars like Heygen, D-ID, Synthesia, Elai, and more
- AI videos and avatars for SEO, onboarding, social media marketing, customer acquisition, explainer videos, branding, and more
- Introduction to Google Colab and the best tools like Wrapfusion, Deforum, Wav2Lip, Faceswap, Deepfake, and more
- Personal projects such as creating, editing & cutting videos with CapCut, Pika, Shotcut
- Pictory and WOXO for the very lazy: Complete videos with one click
- Opus Pro for YouTube Shorts, Instagram, or TikTok
- Insight into Canva and Adobe Express for Instagram Reels and more
- The future of AI videos for the job market
- Copyrights, data protection, and copyright
9. Python and Machine Learning for Complete Beginners
Instructor: John Purcell
Become Part of the Artificial Intelligence Revolution
Course Highlights:
- Rating: 4.59 ⭐ (313 reviews)
- Students Enrolled: 1880
- Course Length: 156457 hours
- Number of Lectures: 465
- Number of Quizzes: 0
Python and Machine Learning for Complete Beginners, has an average rating of 4.59, with 465 lectures, based on 313 reviews, and has 1880 subscribers.
You will learn about Learn how to program in Python Discover machine learning Use artificial intelligence in your programs Learn how to analyse data and make predictions This course is ideal for individuals who are Complete beginners with computer programming or Existing programmers who want to improve their Python knowledge or learn Python or Python programmers who want to learn how to use AI/ML in their programs. It is particularly useful for Complete beginners with computer programming or Existing programmers who want to improve their Python knowledge or learn Python or Python programmers who want to learn how to use AI/ML in their programs.
Learn More About Python and Machine Learning for Complete Beginners
What You Will Learn
- Learn how to program in Python
- Discover machine learning
- Use artificial intelligence in your programs
- Learn how to analyse data and make predictions
8. Machine Learning, Data Science and Generative AI with Python
Instructor: Sundog Education by Frank Kane
Complete hands-on machine learning and GenAI tutorial with data science, Tensorflow, GPT, OpenAI, and neural networks
Course Highlights:
- Rating: 4.64 ⭐ (33544 reviews)
- Students Enrolled: 219186
- Course Length: 72852 hours
- Number of Lectures: 156
- Number of Quizzes: 0
Machine Learning, Data Science and Generative AI with Python, has an average rating of 4.64, with 156 lectures, based on 33544 reviews, and has 219186 subscribers.
You will learn about Build generative AI systems with OpenAI, RAG, and LLM Agents Build artificial neural networks with Tensorflow and Keras Implement machine learning at massive scale with Apache Spark's MLLib Classify images, data, and sentiments using deep learning Make predictions using linear regression, polynomial regression, and multivariate regression 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 This course is ideal for individuals who are 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. or Technologists curious about how deep learning really works or 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. or If you have no prior coding or scripting experience, you should NOT take this course – yet. Go take an introductory Python course first. It is particularly useful 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. or Technologists curious about how deep learning really works or 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. or If you have no prior coding or scripting experience, you should NOT take this course – yet. Go take an introductory Python course first.
Learn More About Machine Learning, Data Science and Generative AI with Python
What You Will Learn
- Build generative AI systems with OpenAI, RAG, and LLM Agents
- Build artificial neural networks with Tensorflow and Keras
- Implement machine learning at massive scale with Apache Spark's MLLib
- Classify images, data, and sentiments using deep learning
- Make predictions using linear regression, polynomial regression, and multivariate regression
- 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
7. Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2024]
Instructor: Kirill Eremenko
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
Course Highlights:
- Rating: 4.54 ⭐ (191747 reviews)
- Students Enrolled: 1100065
- Course Length: 152569 hours
- Number of Lectures: 472
- Number of Quizzes: 37
![Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2024]](https://img-c.udemycdn.com/course/480x270/950390_270f_3.jpg)
Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2024], has an average rating of 4.54, with 472 lectures, 37 quizzes, based on 191747 reviews, and has 1100065 subscribers.
You will learn about Master Machine Learning on Python & R Have a great intuition of many Machine Learning models Make accurate predictions Make powerful analysis Make robust Machine Learning models Create strong added value to your business Use Machine Learning for personal purpose Handle specific topics like Reinforcement Learning, NLP and Deep Learning Handle advanced techniques like Dimensionality Reduction Know which Machine Learning model to choose for each type of problem Build an army of powerful Machine Learning models and know how to combine them to solve any problem This course is ideal for individuals who are Anyone interested in Machine Learning. or Students who have at least high school knowledge in math and who want to start learning Machine Learning. or Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning. or Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets. or Any students in college who want to start a career in Data Science. or Any data analysts who want to level up in Machine Learning. or Any people who are not satisfied with their job and who want to become a Data Scientist. or Any people who want to create added value to their business by using powerful Machine Learning tools. It is particularly useful for Anyone interested in Machine Learning. or Students who have at least high school knowledge in math and who want to start learning Machine Learning. or Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning. or Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets. or Any students in college who want to start a career in Data Science. or Any data analysts who want to level up in Machine Learning. or Any people who are not satisfied with their job and who want to become a Data Scientist. or Any people who want to create added value to their business by using powerful Machine Learning tools.
Learn More About Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2024]
What You Will Learn
- Master Machine Learning on Python & R
- Have a great intuition of many Machine Learning models
- Make accurate predictions
- Make powerful analysis
- Make robust Machine Learning models
- Create strong added value to your business
- Use Machine Learning for personal purpose
- Handle specific topics like Reinforcement Learning, NLP and Deep Learning
- Handle advanced techniques like Dimensionality Reduction
- Know which Machine Learning model to choose for each type of problem
- Build an army of powerful Machine Learning models and know how to combine them to solve any problem
6. Tensorflow 2.0: Deep Learning and Artificial Intelligence
Instructor: Lazy Programmer Inc.
Machine Learning & Neural Networks for Computer Vision, Time Series Analysis, NLP, GANs, Reinforcement Learning, +More!
Course Highlights:
- Rating: 4.78 ⭐ (12918 reviews)
- Students Enrolled: 58750
- Course Length: 85904 hours
- Number of Lectures: 169
- Number of Quizzes: 0
Tensorflow 2.0: Deep Learning and Artificial Intelligence, has an average rating of 4.78, with 169 lectures, based on 12918 reviews, and has 58750 subscribers.
You will learn about Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs) Predict Stock Returns Time Series Forecasting Computer Vision How to build a Deep Reinforcement Learning Stock Trading Bot GANs (Generative Adversarial Networks) Recommender Systems Image Recognition Convolutional Neural Networks (CNNs) Recurrent Neural Networks (RNNs) Use Tensorflow Serving to serve your model using a RESTful API Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices Use Tensorflow's Distribution Strategies to parallelize learning Low-level Tensorflow, gradient tape, and how to build your own custom models Natural Language Processing (NLP) with Deep Learning Demonstrate Moore's Law using Code Transfer Learning to create state-of-the-art image classifiers Earn the Tensorflow Developer Certificate Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion This course is ideal for individuals who are Beginners to advanced students who want to learn about deep learning and AI in Tensorflow 2.0 It is particularly useful for Beginners to advanced students who want to learn about deep learning and AI in Tensorflow 2.0.
Learn More About Tensorflow 2.0: Deep Learning and Artificial Intelligence
What You Will Learn
- Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
- Predict Stock Returns
- Time Series Forecasting
- Computer Vision
- How to build a Deep Reinforcement Learning Stock Trading Bot
- GANs (Generative Adversarial Networks)
- Recommender Systems
- Image Recognition
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Use Tensorflow Serving to serve your model using a RESTful API
- Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices
- Use Tensorflow's Distribution Strategies to parallelize learning
- Low-level Tensorflow, gradient tape, and how to build your own custom models
- Natural Language Processing (NLP) with Deep Learning
- Demonstrate Moore's Law using Code
- Transfer Learning to create state-of-the-art image classifiers
- Earn the Tensorflow Developer Certificate
- Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion
5. [NEW] Ultimate AWS Certified AI Practitioner AIF-C01
Instructor: Stephane Maarek | AWS Certified Cloud Practitioner,Solutions Architect,Developer
Practice Exam included + explanations | Learn Artificial Intelligence | Pass the AWS AI Practitioner AIF-C01 exam!
Course Highlights:
- Rating: 4.75 ⭐ (6952 reviews)
- Students Enrolled: 45552
- Course Length: 36442 hours
- Number of Lectures: 147
- Number of Quizzes: 10
![[NEW] Ultimate AWS Certified AI Practitioner AIF-C01](https://img-c.udemycdn.com/course/480x270/6082775_2db5_3.jpg)
[NEW] Ultimate AWS Certified AI Practitioner AIF-C01, has an average rating of 4.75, with 147 lectures, 10 quizzes, based on 6952 reviews, and has 45552 subscribers.
You will learn about Pass the AWS Certified AI Practitioner Certification AIF-C01 Practice Exam with Explanations included! Learn the Fundamentals of Artificial Intelligence, Machine Learning, Deep Learning & Generative AI Learn the key AWS AI services, including a deep dive on Bedrock, Amazon Q and SageMaker Learn Prompt Engineering All 200+ slides available as downloadable PDF This course is ideal for individuals who are Anyone wanting to acquire the knowledge to pass the AWS Certified AI Practitioner Certification or Having an IT background will strongly help It is particularly useful for Anyone wanting to acquire the knowledge to pass the AWS Certified AI Practitioner Certification or Having an IT background will strongly help.
Learn More About [NEW] Ultimate AWS Certified AI Practitioner AIF-C01
What You Will Learn
- Pass the AWS Certified AI Practitioner Certification AIF-C01
- Practice Exam with Explanations included!
- Learn the Fundamentals of Artificial Intelligence, Machine Learning, Deep Learning & Generative AI
- Learn the key AWS AI services, including a deep dive on Bedrock, Amazon Q and SageMaker
- Learn Prompt Engineering
- All 200+ slides available as downloadable PDF
4. Intro to AI: A Beginner’s Guide to Artificial Intelligence
Instructor: 365 Careers
Understand How AI Works and How to Leverage This Technology to Transform Your Business and Career
Course Highlights:
- Rating: 4.58 ⭐ (140 reviews)
- Students Enrolled: 941
- Course Length: 9016 hours
- Number of Lectures: 42
- Number of Quizzes: 4
Intro to AI: A Beginner's Guide to Artificial Intelligence, has an average rating of 4.58, with 42 lectures, 4 quizzes, based on 140 reviews, and has 941 subscribers.
You will learn about Understand key Artificial Intelligence concepts and build a solid foundation Skyrocket productivity using AI Understand Generative AI and the underlying technology Grasp the importance of AI ethics Acquire an understanding of key AI tools Become acquainted with the top job prospects in the AI field This course is ideal for individuals who are This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills It is particularly useful for This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.
Learn More About Intro to AI: A Beginner's Guide to Artificial Intelligence
What You Will Learn
- Understand key Artificial Intelligence concepts and build a solid foundation
- Skyrocket productivity using AI
- Understand Generative AI and the underlying technology
- Grasp the importance of AI ethics
- Acquire an understanding of key AI tools
- Become acquainted with the top job prospects in the AI field
3. The AI Engineer Course 2024: Complete AI Engineer Bootcamp
Instructor: 365 Careers
Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs
Course Highlights:
- Rating: 4.55 ⭐ (505 reviews)
- Students Enrolled: 5747
- Course Length: 77556 hours
- Number of Lectures: 325
- Number of Quizzes: 123
The AI Engineer Course 2024: Complete AI Engineer Bootcamp, has an average rating of 4.55, with 325 lectures, 123 quizzes, based on 505 reviews, and has 5747 subscribers.
You will learn about The course provides the entire toolbox you need to become an AI Engineer Understand key Artificial Intelligence concepts and build a solid foundation Start coding in Python and learn how to use it for NLP and AI Impress interviewers by showing an understanding of the AI field Apply your skills to real-life business cases Harness the power of Large Language Models Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components Become familiar with Hugging Face and the AI tools it offers Use APIs and connect to powerful foundation models This course is ideal for individuals who are You should take this course if you want to become an AI Engineer or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills It is particularly useful for You should take this course if you want to become an AI Engineer or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.
Learn More About The AI Engineer Course 2024: Complete AI Engineer Bootcamp
What You Will Learn
- The course provides the entire toolbox you need to become an AI Engineer
- Understand key Artificial Intelligence concepts and build a solid foundation
- Start coding in Python and learn how to use it for NLP and AI
- Impress interviewers by showing an understanding of the AI field
- Apply your skills to real-life business cases
- Harness the power of Large Language Models
- Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components
- Become familiar with Hugging Face and the AI tools it offers
- Use APIs and connect to powerful foundation models
2. Artificial Intelligence and Machine Learning: Complete Guide
Instructor: Jones Granatyr
Do you want to study AI and don’t know where to start? You will learn everything you need to know in theory and practice
Course Highlights:
- Rating: 4.64 ⭐ (178 reviews)
- Students Enrolled: 2362
- Course Length: 79962 hours
- Number of Lectures: 189
- Number of Quizzes: 0
Artificial Intelligence and Machine Learning: Complete Guide, has an average rating of 4.64, with 189 lectures, based on 178 reviews, and has 2362 subscribers.
You will learn about The theoretical and practical basis of the main Artificial Intelligence algorithms Implement Artificial Intelligence algorithms from scratch and using pre-defined libraries Learn the intuition and practice about machine learning algorithms for classification, regression, association rules, and clustering Learn Machine Learning without knowing a single line of code Use Orange visual tool to create, analyze and test algorithms Use Python programming language to create Artificial Intelligence algorithms Learn the basics of programming in Python Use greedy search and A* (A Star) algorithms to find the shortest path between cities Implement optimization algorithms for minimization and maximization problems Implement an AI to predict the amount of tip to be given in a restaurant, using fuzzy logic Use data exploration techniques applied to a COVID-19 disease database Create a reinforcement learning agent to simulate a taxi that needs to learn how to pick up and drop off passengers Implement artificial neural networks and convolutional neural networks to classify images of the characters Homer and Bart, from the Simpsons cartoon Learn natural language processing techniques and create a sentiment classifier Detect and recognize faces using computer vision techniques Track objects in video using computer vision Generate new images that do not exist in the real world using Artificial Intelligence This course is ideal for individuals who are People interested in starting their studies in Artificial Intelligence, Machine Learning, Data Science or Deep Learning or People who want to study Artificial Intelligence, however, don't know where to start or Undergraduate students studying subjects related to Artificial Intelligence or Anyone interested in Artificial Intelligence or Entrepreneurs who want to apply machine learning to commercial projects or Entrepreneurs who want to create efficient solutions to real problems in their companies It is particularly useful for People interested in starting their studies in Artificial Intelligence, Machine Learning, Data Science or Deep Learning or People who want to study Artificial Intelligence, however, don't know where to start or Undergraduate students studying subjects related to Artificial Intelligence or Anyone interested in Artificial Intelligence or Entrepreneurs who want to apply machine learning to commercial projects or Entrepreneurs who want to create efficient solutions to real problems in their companies.
Learn More About Artificial Intelligence and Machine Learning: Complete Guide
What You Will Learn
- The theoretical and practical basis of the main Artificial Intelligence algorithms
- Implement Artificial Intelligence algorithms from scratch and using pre-defined libraries
- Learn the intuition and practice about machine learning algorithms for classification, regression, association rules, and clustering
- Learn Machine Learning without knowing a single line of code
- Use Orange visual tool to create, analyze and test algorithms
- Use Python programming language to create Artificial Intelligence algorithms
- Learn the basics of programming in Python
- Use greedy search and A* (A Star) algorithms to find the shortest path between cities
- Implement optimization algorithms for minimization and maximization problems
- Implement an AI to predict the amount of tip to be given in a restaurant, using fuzzy logic
- Use data exploration techniques applied to a COVID-19 disease database
- Create a reinforcement learning agent to simulate a taxi that needs to learn how to pick up and drop off passengers
- Implement artificial neural networks and convolutional neural networks to classify images of the characters Homer and Bart, from the Simpsons cartoon
- Learn natural language processing techniques and create a sentiment classifier
- Detect and recognize faces using computer vision techniques
- Track objects in video using computer vision
- Generate new images that do not exist in the real world using Artificial Intelligence
1. Complete A.I. & Machine Learning, Data Science Bootcamp
Instructor: Andrei Neagoie
Learn Data Science, Data Analysis, Machine Learning (Artificial Intelligence) and Python with Tensorflow, Pandas & more!
Course Highlights:
- Rating: 4.61 ⭐ (24713 reviews)
- Students Enrolled: 134102
- Course Length: 155778 hours
- Number of Lectures: 384
- Number of Quizzes: 2
Complete A.I. & Machine Learning, Data Science Bootcamp, has an average rating of 4.61, with 384 lectures, 2 quizzes, based on 24713 reviews, and has 134102 subscribers.
You will learn about Become a Data Scientist and get hired Master Machine Learning and use it on the job Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0 Use modern tools that big tech companies like Google, Apple, Amazon and Meta use Present Data Science projects to management and stakeholders Learn which Machine Learning model to choose for each type of problem Real life case studies and projects to understand how things are done in the real world Learn best practices when it comes to Data Science Workflow Implement Machine Learning algorithms Learn how to program in Python using the latest Python 3 How to improve your Machine Learning Models Learn to pre process data, clean data, and analyze large data. Build a portfolio of work to have on your resume Developer Environment setup for Data Science and Machine Learning Supervised and Unsupervised Learning Machine Learning on Time Series data Explore large datasets using data visualization tools like Matplotlib and Seaborn Explore large datasets and wrangle data using Pandas Learn NumPy and how it is used in Machine Learning A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided Learn to use the popular library Scikit-learn in your projects Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry Learn to perform Classification and Regression modelling Learn how to apply Transfer Learning This course is ideal for individuals who are Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science and Python or You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable or Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field or You’re looking for one single course to teach you about Machine learning and Data Science and get you caught up to speed with the industry or You want to learn the fundamentals and be able to truly understand the topics instead of just watching somebody code on your screen for hours without really “getting it” or You want to learn to use Deep learning and Neural Networks with your projects or You want to add value to your own business or company you work for, by using powerful Machine Learning tools. It is particularly useful for Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science and Python or You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable or Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field or You’re looking for one single course to teach you about Machine learning and Data Science and get you caught up to speed with the industry or You want to learn the fundamentals and be able to truly understand the topics instead of just watching somebody code on your screen for hours without really “getting it” or You want to learn to use Deep learning and Neural Networks with your projects or You want to add value to your own business or company you work for, by using powerful Machine Learning tools.
Learn More About Complete A.I. & Machine Learning, Data Science Bootcamp
What You Will Learn
- Become a Data Scientist and get hired
- Master Machine Learning and use it on the job
- Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
- Use modern tools that big tech companies like Google, Apple, Amazon and Meta use
- Present Data Science projects to management and stakeholders
- Learn which Machine Learning model to choose for each type of problem
- Real life case studies and projects to understand how things are done in the real world
- Learn best practices when it comes to Data Science Workflow
- Implement Machine Learning algorithms
- Learn how to program in Python using the latest Python 3
- How to improve your Machine Learning Models
- Learn to pre process data, clean data, and analyze large data.
- Build a portfolio of work to have on your resume
- Developer Environment setup for Data Science and Machine Learning
- Supervised and Unsupervised Learning
- Machine Learning on Time Series data
- Explore large datasets using data visualization tools like Matplotlib and Seaborn
- Explore large datasets and wrangle data using Pandas
- Learn NumPy and how it is used in Machine Learning
- A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
- Learn to use the popular library Scikit-learn in your projects
- Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry
- Learn to perform Classification and Regression modelling
- Learn how to apply Transfer Learning
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