AI Programming with Python : A Course For Beginners
Introduction
AI Programming with Python is a comprehensive course that teaches students a combination of AI programming with Python, AI, and machine learning fundamentals with theory-based lectures, reading material, and some hands-on exercises and projects. This course offers flexible learning opportunities for students to learn at their own pace. Moreover, the hands-on project can work as a portfolio that can be shown as experience.
What Will You Gain From This Course?
Following the completion of this course, the students will be able to:
- Learn about the fundamental concepts within AI programming with Python, its algorithm, and ways to manipulate and interact with AI programming with Python technology
- Get familiar with Python; build a solid understanding of Python programming, including its syntax, data structures, and control flow.
- Explore some of the important AI and machine learning concepts as well as explore important fundamentals such as supervised and unsupervised learning, neural networks, and AI programming with Python.
- Polish the practical skills in AI that are required for people working in the fields of Python programming, AI, and machine learning.
- Earn hands-on experience by working with some advanced AI techniques for real-world problems, including building and training AI models.
- Learn about different ways of data analysis, data management as well as data representation.
- Learn some of the best tools used for data visualization like NumPy, Pandas, and Matplotlib as well as use data using Python libraries for better data management.
- Get familiar with natural language processing techniques that are used for processing and understanding human language.
Skills Acquired:
- Model Evaluation
- AI Programming with Python
- Markov
- Hyperparameter Tuning
- Cyclegan
- Linear Algebra
Who Can Benefit From This Course?
This course is designed for:
- People working in the tech department who want to know more about AI, AI Programming with Python, and machine learning.
- Data scientists who are currently working with different data sets and want to automate their work by using AI and machine learning techniques for data analysis.
- Software engineers, tech experts, and developers looking for ways to incorporate AI and machine learning into their applications and current projects.
- Machine learning enthusiasts, especially people working as AI experts and AI developers passionate about AI and machine learning and want to polish their practical skills.
Course Content
8 courses – Certificate of Completion
Introduction to AI Programming
The first course in this learning program will take nearly two hours and it is further divided into three lessons. The first lesson within this course offers an introduction to AI Programming with the Python. The second lesson helps the students to start challenging themselves by setting a path toward a rewarding journey and this lesson will mainly help the students learn about different projects and important content. Finally, the third lesson addresses important queries related to accounts or general questions about the program.
Introduction to Python for AI Programmers
The second course of this training program will take around one month to complete and consist of eight lessons. This module focuses on coding with Python, drawing up libraries and automation scripts to solve complex problems quickly. The first lesson of this course offers an introduction to Python Programming for AI and its importance. The second lesson mainly focuses on the use of Python Data Types and Operators in AI Programming. The students will not just get the basic guide but will also get to know about data types and operators, built-in functions, type conversion, whitespace, and style guidelines.
The third lesson in this course focus mainly on the Python data structures in AI programming especially the use of data structures to order and group different data types together, along with more useful built-in functions and operators. The fourth lesson in this course focuses on using control flow in AI programming, conditional statements, repeating code with loops and useful built-in functions, and list comprehensions. The fifth lesson of this course is dedicated to using Python functions in AI programming, especially functions, variable scope, documentation, lambda expressions, iterators, and generators. The sixth lesson in this course sheds light on Python scripting for AI programming, especially good scripting practices, interacting with different inputs, and discovering awesome tools. Finally, the last two lessons wrap up the course by focusing on object-oriented Python for AI programming and some hands-on projects to use Python code and a created image classifier to identify dog breeds.
Numpy, Pandas, Matplotlib
The third course within this program takes around two weeks to complete. The students will get to learn about library packages for Python, such as Numpy, which helps with adding support for large data, Pandas used for data manipulation and analysis, as well as Matplotlib used for data visualization. The first lesson within this course talks about Anaconda, which is a package and environment manager built specifically for data. The second lesson focuses on Jupyter Notebooks, which is another very important tool for getting started with writing Python code. The third lesson is mainly focused on NumPy and covers its basics and utility. The fourth lesson of this course covers the basics of the Pandas Series especially DataFrames and its utility load and process data. The last two lessons of this course focus on Matplotlib and Seaborn so the students can find out ways to visualize your data.
Linear Algebra Essentials
The fourth course in this learning program will take around two weeks and focuses on Linear Algebra Essentials. The students will get to know about the important mathematical tools in the world of AI. The first lesson of this course only offers an introduction to Linear Algebra and its importance. The second lesson explores vectors as the basic building block of Linear Algebra. The third lesson describes Linear Combination especially different ways to scale and add vectors as well as ways to visualize the process. The fourth lesson mainly looks at Linear Transformation and Matrices, so the students can get to know more about the ways to apply the math and visualize the concept. The fifth lesson helps the students to Learn about converting the graph to 2D vectors. The sixth lesson focuses on Linear Combination Lab especially computationally determining a vector's span and ways to solve a simple system of equations. The seventh lesson mainly explores Linear Mapping Lab while the eighth lesson is all about Neural Networks and their relation with Linear Algebra.
Calculus Essentials
The fifth course in this learning program is all about Calculus, especially its foundation, training a neural network i.e. plotting, derivatives, and the chain rule, etc. Overall, this course will require three hours to complete. The first lesson of this course is all about Calculus, whereas the second lesson mainly focuses on Calculus in Neural Networks.
Neural Networks - AI Programming with Python
The sixth course of this training program explains the use of algorithms inspired by the human brain operating and using different concepts for neural networks to solve problems. This course will mainly take three weeks to complete. The first lesson within this course only offers a basic introduction to Neural Networks whereas the second lesson explores the solid foundations of AI Programming with Python and neural networks. Within a course the third lesson is all about Implementing Gradient Descent, so the students can know about error function and gradient descent via Numpy matrix multiplication. The fourth lesson mainly focuses on Training Neural Networks, whereas the fifth Lesson explores AI Programming with Python with PyTorch.
Programming Transformer Neural Networks with PyTorch
This is the seventh course in this AI Programming with Python program and will require nearly four hours to complete. This course will help the students learn about the essential concepts of Transformer Neural Networks and their use via PyTorch. The first lesson of this course offers a basic Introduction to Transformer Neural Networks especially concepts like NLP basics, tokenization, and model training using PyTorch for AI advancements. The second lesson focuses on Building Transformer Neural Networks with PyTorch especially tokenization, embeddings, multi-head attention, training, and text generation for NLP tasks. The third lesson of this course helps with using pre-trained transformers, especially training, fine-tuning, limitations, and applying them to NLP tasks like text generation and QA.
Create Your Own Image Classifier
The eighth and last course of this training program will require four hours to complete and consist of just one project. The students will be able to create his or her own art image classification application with the help of Python.
Description
The AI Programming with Python course by Udacity is one of the simplest and easy to understand courses that anyone can learn from. This course covers the utility of artificial intelligence and some of the AI Programming with Python fundamentals as well. This course has eight main courses and each course further has multiple lessons tackling different topics.
Through this course, the students can expect to know more about Building and designing neural networks, using AI Programming with Python frameworks i.e. TensorFlow and PyTorch, Applying AI for problem-solving, and some advanced techniques in AI.
Meet the Instructor
Udacity
Udacity is a leading online learning platform that offers a wide range of courses and Nanodegree programs designed to equip learners with the skills needed to succeed in today's rapidly evolving technological landscape. Founded with the mission to democratize education, Udacity has become a trusted source for high-quality, industry-relevant learning experiences.