List of courses to Dominate Artificial Intelligence
In recent years we are witnessing an incessant development of artificial intelligence, which is having an ever greater and more important impact on our lives.
Now our daily life is surrounded by this technology, and our future will be even more so thanks to all the possible uses of Artificial Intelligence, starting from the medical field, where it is possible to analyze the historical data of patients and improve the phases of diagnosis and much more, up to self-driving cars, which are already becoming part of our lives, and much more
The size of the global artificial intelligence market was valued at $ 39.9 billion in 2019 and is expected to grow at an annual rate of 42.2% from 2020 to 2027, and according to some estimates, the size of this market will arrive at $252 billion by 2023 and a whopping $ 350 billion by 2025
You may be wondering, what is the goal of this list? the goal is to make sure that everyone can enter this world of the future with the right knowledge and make sure that everyone can participate, understand, and collaborate in the next technological revolution, so the list covers most of the topics concerning artificial intelligence, starting from mathematical and computer requirements up to real artificial intelligence
Linear Algebra:
- Linear Algebra | Khan Academy
What you’ll learn in this Course:
- Vector, linear combinations and spans, linear dependence and independence
- Functions and linear transformations, transformations, and matrix multiplication
- Orthogonal complements, orthogonal projections, change of basis
2. Linear Algebra – Foundations to Frontiers | Edx
What you’ll learn in this Course:
- Connections between linear transformations, matrices, and systems of linear equations
- Partitioned matrices and characteristics of special matrices
- Algorithms for matrix computations and solving systems of equations
- Vector spaces, subspaces, and characterizations of linear independence
- Orthogonality, linear least-squares, eigenvalues, and eigenvectors
Calculus:
- Calculus 1A: Differentiation | Edx
What you’ll learn in this Course:
- How to evaluate limits graphically and numerically
- The physical meaning, and geometric interpretation of the derivative
- To calculate the derivative of any function
- To sketch many functions by hand
- To make linear and quadratic approximations of functions
- To apply derivatives to maximize and minimize functions and find related rates
2. Differential Calculus| Khan Academy
What you’ll learn in this Course:
- Limits and continuity
- Derivates: chain rule and other advanced topics
- Applications of derivatives
- Analyzing functions
- Parametric equations, polar coordinates, and vector-valued functions
3. Multivariable Calculus| Khan Academy
What you’ll learn in this Course:
- Derivates of multivariable functions
- Derivates: chain rule and other advanced topics
- Applications of multivariable derivatives
- Integrating multivariable functions
- Green’s, Stokes’, and the divergence theorems
Statistics and probability:
- Statistics and Probability | Khan Academy
What you’ll learn in this Course:
- Analyzing Categorical Data
- Displaying, comparing, and Summarizing quantitative data
- Modeling data distributions, exploring bivariate numerical data
- Study design
- Probability
- Counting, permutations, and combinations, random variables
- Sampling distributions, confidence intervals
- Significance tests, inference for categorical data
Computer Science:
- CS50’s Introduction to Computer Science| Edx
What you’ll learn in this Course:
- A broad and robust understanding of computer science and programming
- How to think algorithmically and solve programming problems efficiently
- Concepts like abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development
- Familiarity in several languages, including C, Python, SQL, and JavaScript plus CSS and HTML
Python programming:
Python is one of the most growing and popular programming languages of recent years and has managed to become the main language used for the development of artificial intelligence, thanks to its enormous simplicity and the many libraries and frameworks that have been developed, which allow you to do a lot with very few lines of code
Python Bootcamps | Udemy
This can most likely be one of the best and most comprehensive online courses when it comes to learning Python
What you’ll learn in this Course:
- Learn to use Python professionally, learning both Python 2 and Python 3
- Create games with Python, like Tic Tac Toe and Blackjack
- Learn advanced Python features, like the collections module and how to work with timestamps
- Learn to use Object Oriented Programming with classes
- Understand complex topics, like decorators.
- Understand how to use both the Jupyter Notebook and create .py files
- Get an understanding of how to create GUIs in the Jupyter Notebook system
Python Tutorial | tutorialspoint
On this site you will be able to learn everything there is to know about Python, it can be a good choice to accompany the course listed above
Data Structure and Algorithms
The knowledge of the main data structures and the main algorithms can be very useful for understanding artificial intelligence more deeply
Learn Data Structure and Algorithms | programiz
What you’ll learn in this Course:
- Data Structure: Stack, Queue, Linked List, Hash table, Binary Tree, many other
- Storting, searching, and Greedy Algorithms
2. Algorithms | Khan Academy
What you’ll learn in this Course:
- Intro to algorithms
- Binary Search, asymptotic notation
- Selection sort, insertion sort, merge sort, quick sort
- recursive algorithms, graph representation
- Breadth-first search
Artificial Intelligence:
AI For Everyone | Coursera
This course is largely non-technical and is intended for those who do not need to learn in-depth AI technicalities but who wish to learn how to better use AI in their organizations or launch AI initiatives or work with an intelligence team. artificial
It’s also a great course for engineers, programmers, and people with technical backgrounds to learn the business aspects of AI. It is very informative and detailed for beginners who don’t know anything about artificial intelligence. This artificial intelligence course begins with a comprehensive overview of what artificial intelligence is and finally continues by discussing the entire AI project workflow and how to develop an AI strategy for your business. What you’ll learn in this Course:
- Overview of what AI is
- The meaning behind common AI terminology
- A realistic view of AI and what it can and cannot do with examples
- How to spot opportunities to apply AI to challenges and problems in your organization
- How to build AI in your company
- Ethical and societal concerns and discussions surrounding AI
CS50’s Introduction to Artificial Intelligence with Python | Edx
This course explores the concepts and algorithms behind modern artificial intelligence, diving into the ideas that give rise to technologies such as game engines, handwriting recognition, and machine translation.
What you’ll learn in this Course:
- graph search algorithms. adversarial search
- knowledge representation, logical inference
- probability theory. Bayesian networks
- Markov models, constraint satisfaction
- machine learning, reinforcement learning, neural networks, natural language processing
Artificial Intellegnce | Edx
This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems
You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.
What you’ll learn in this Course:
- Introduction to Artificial Intelligence and intelligent agents, history of Artificial Intelligence
- Building intelligent agents (search, games, logic, constraint satisfaction problems)
- Machine Learning algorithms
- Applications of AI (Natural Language Processing, Robotics/Vision)
- Solving real AI problems through programming with Python
Machine Learning | Coursera
This Stanford Machine Learning Course has been created by Andrew Ng, the most renowned expert in AI and Machine Learning, co-founder of Coursera, founding lead of Google’s deep learning research unit Google Brain, former head of AI at Baidu, and currently CEO at Landing AI
The popularity of this ML course can be gauged from the fact that around 3.5 million students and professionals have already taken this course and 93% of them have given it a 5-star rating
This course introduces learners to the core ideas of machine learning, data mining, and statistical pattern recognition. It imparts them a good grounding in the mathematical, statistical, and computer science fundamentals that form the basis of automated learning machines
What you’ll learn in this Course:
- Review of linear algebra
- Linear Regression with one and multiple variables, and Logistic Regression
- Supervised Learning
- Support Vector Machines
- Neural Networks, and Backpropagation algorithm for neural networks
- Unsupervised Learning
- Dimensionality Reduction
- Anomaly Detection
- Recommender algorithms
- Deep Learning
- Applying machine learning algorithms with large datasets
Python for Data Science and Machine Learning Bootcamp | Udemy
This course is one of the most popular that can be found on Udemy for Machine Learning and Data Science with Python
It teaches to work with the most popular Python libraries, such as NumPy, Pandas, Matplotlib, SciKit-Learn, and many more. It also teaches, both theoretically and practically, how the most famous Machine Learning algorithms work
What you’ll learn in this Course:
- Use Python for Data Science and Machine Learning and use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy, Pandas, Matplotlib, Seaborn, Plotly, and SciKit-Learn
- K-Means Clustering, Logistic Regression, Linear Regression, Random Forest and Decision Trees
- Natural Language Processing and Spam Filters
- Neural Networks
- Support Vector Machines
Machine Learning A-Z | Udemy
This is probably the most bought course, and certainly one of the most popular, on Udemy when it comes to artificial intelligence. As the course is designed by two professional Data Scientists, it is broad in terms of content. At the same time, it is organized in such a way that students of all levels can easily grasp the concepts
The course is most recommended for beginners with no previous experience, offers a good and solid overview of machine learning, plus course presents a good balance between theory and practical work
What you’ll learn in this Course:
- Data Processing
- Regression, Classification, Clustering, Association Rule Learning
- Reinforcement Learning, Deep Learning, Dimensionality Reduction
Machine Learning | Edx
This course teaches the essentials of machine learning and algorithms, including supervised learning techniques for regression and classification, unsupervised learning techniques for data modeling and analysis, probabilistic versus non-probabilistic modeling, and optimization and inference algorithms
What you’ll learn in this Course:
- Supervised learning techniques for regression and classification
- Unsupervised learning techniques for data modeling and analysis
- Probabilistic versus non-probabilistic viewpoints
- Optimization and inference algorithms for model learning
Deep Learning Specialization | Coursera
In this course, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects
You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory but also see how it is applied in industry. You will practice all these ideas in Python and TensorFlow
What you’ll learn in this Course:
- Foundations of Deep Learning and how to build neural Network
- Convolutional Network, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more
Deep Learning A-Z | Udemy
This course is one of the best Deep Learning courses you can find on Udemy, it covers the basic topics of this branch of Machine Learning, talking about the different types of neural networks and many other topics
What you’ll learn in this Course:
- Artificial Neural Network, Convolutional Neural Network, and Recurrent Neural Network
- Self Organizing Maps, Boltzmann Machines, AutoEncoders
Deep Learning A-Z | Udemy
Reinforcement Learning is an entirely different paradigm in AI and Machine Learning. It has given us amazing insights both in behavioral psychology and neuroscience and is the closest thing we have so far to a true general artificial intelligence
This course is one of the best AI courses out there on Reinforcement Learning. It gives learners a primer on AI-powered reinforcement learning, with a particular focus on stock trading and online advertising. It gives insights into AI techniques that one would never see in traditional supervised machine learning, unsupervised machine learning, or even deep learning
This course is the best fit for those who already have basic knowledge of theoretical and technical aspects of AI and want to understand Reinforcement learning thoroughly. Since it teaches advanced level concepts, the students are expected to know Calculus, Probability, Object-oriented programming, Python coding, Numpy coding, Linear regression, Gradient descent, etc.
What you’ll learn in this Course:
- The multi-armed bandit problem and the explore-exploit dilemma
- Ways to calculate means and moving averages and their relationship to stochastic gradient descent
- Markov Decision Processes (MDPs)
- Dynamic Programming
- Monte Carlo
- Temporal Difference (TD) Learning (Q-Learning and SARSA)
- Approximation Methods
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We have finally reached the end of the list, I hope it is useful for you and that it can inspire you and push you to face this long learning path on a technology that will lay the foundations of our future as a species
Finally, if you have any questions or suggestions, feel free to leave them in the comments below.