Introduction to AI, ML, and DL Using Python

Become an " AI, ML, and DL" Specialist. In this learning path, you will learn " Types of Artificial Intelligence, Applications of Machine Learning, Supervised, Unsupervised Learning, Different types of Algorithms, Pandas, Artificial Neural Networks, CNN's, RNN's, GAN's and Many More".

1000+ Students enrolled
Flexible Learning

Learn at your own pace and reach your personal goals on the schedule that works best for you.

Real-world Projects

You’ll master the in-demand technologies by building real-world projects.

Live Mentor Workshops

You’ll have access to free live mentor workshop sessions through out your subscription period.

Verifiable Certificate

Upon successful completion of the Course, You will receive a Verifiable certificate with QR code.

Quiz & Mock Tests

Assess your knowledge with quiz's, mock tests and interviews.

Assured Internship

Upon successful completion of this course you are eligible to grab an internship opportunity.

Introduction to AI, ML, and DL Using Python

Become an " AI, ML, and DL" Specialist. In this learning path, you will learn " Types of Artificial Intelligence, Applications of Machine Learning, Supervised, Unsupervised Learning, Different types of Algorithms, Pandas, Artificial Neural Networks, CNN's, RNN's, GAN's and Many More".

Login to Subscribe
Includes:
  • Verifiable certificate
  • Quiz & mock tests
  • Live mentor workshops
  • 2 devices access*
Course Description

Welcome to " Introduction to AI, ML, and DL Using Python"

In this course you will be learning “Types of Artificial Intelligence, Applications of Machine Learning, Supervised, Unsupervised Learning, Different types of Algorithms, Pandas, Artificial Neural Networks, CNN's, RNN's, GAN's and Many More”. We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed in the industry. This course has a tremendous amount of content and resources so that you can learn everything you need to know - whatever is appropriate for your ability level. You will be able to learn at your own pace. You will always be able to come back to the content to review it or learn additional concepts when you are ready for them. You will get great value from this course and, more importantly, you will have a great time learning.

Happy Learning

What you will learn?
  • Introduction to Artificial Intelligence
  • Types of Artificial Intelligence
  • Heuristic Search Techniques
  • A star algorithm
  • Applications of Machine Learning
  • Clustering
  • Classifiers
  • What is Python and its applications
  • Introduction to NumPy
  • Introduction to Pandas
  • Visualization of Data
  • Artificial Neural Networks
  • Backpropagation in ANNs
  • Optimizers
  • Regularization Techniques
  • Difference between CNN's and ANN's
  • Applications of CNNs
  • Introduction to RNNs
  • Different Types of RNNs
  • Brief Introduction to GRU's and LSTM's
  • Autoencoders in PyTorch
  • Introduction to GANs
  • GANs in PyTorch
Requirements
  • No Prerequisites Required
Course Curriculum
  • Module - 1: AI/ML Basics
    Introductions to AI/ML and DL. In this week you will learn "Introduction to Artificial Intelligence, Heuristic Search Techniques, What is Machine Learning, Clustering and Many More"
    Section 1: Introduction
    15 Lessons
    • Introduction to Artificial Intelligence
    • Types of Artificial Intelligence
    • Subsets of Artificial Intelligence
    • Heuristic Search Techniques
    • A Star algorithm
    • What is Machine Learning
    • Applications of Machine Learning
    • Simple two class problem in Machine Learning
    • Classification and Regression
    • Clustering
    • Supervised and Unsupervised Learning
    • Reinforcement Learning
    • Classifiers
    • Clustering Algorithms
    • Quiz
  • Module - 2: Basic Python for AI/ML
    Go Zero-One by learning the much-needed fundamentals of “Python". In this course, you will learn "What is Python and its applications, Python variables, input, and output, Lists, and Tuples, Iterators, and collections, and Many More"
    Section 1: Python
    11 Lessons
    • What is Python and its applications
    • Python variables, input and output
    • Swapping two variables in Python
    • For loops and if conditions
    • Lists and Tuples
    • Sets in Python
    • Dictionaries in Python
    • Object Oriented Programming
    • Math library in Python
    • Iterators, Itertools and Collections
    • Quiz
  • Module - 3: NumPy - Python Libraries
    Introductions to AI/ML and DL. In this week you will learn "Introduction to NumPy, Introduction to Pandas, Visualization of Data and Introduction to scikit-learn"
    Section 1: Python Libraries
    5 Lessons
    • Introduction to NumPy
    • Introduction to Pandas
    • Visualization of Data
    • Introduction to scikit-learn
    • Quiz
  • Module - 4: Artificial Neural Networks
    Introductions to AI/ML and DL. In this week you will learn "Artificial Neural Networks, Backpropagation in ANNs, Activation Functions, Loss Functions, Optimizers, XOR Problem in NumPy and Many More"
    Section 1: Introduction to Artificial Intelligence
    17 Lessons
    • Artificial Neural Networks
    • Implementation of Artificial Neural Networks
    • Backpropagation in ANNs
    • Activation Functions
    • Loss Functions
    • Batches and Mini-Batches
    • Optimizers
    • Regularization Techniques
    • Initialization of Weights and Biases
    • Machine Learning Frameworks
    • Introduction to Google Colaboratory
    • XOR Problem in NumPy
    • Titanic Classification in Numpy
    • Titanic Classification in TensorFlow
    • Titanic Classification in PyTorch
    • Titanic Classification in Keras
    • Quiz
  • Module - 5: CNN
    Go Zero-One by learning the much-needed fundamentals of “CNN's". In this course, you will learn " What is Convolution, How do CNNs work, Applications of CNN's, Optimizing CNN's and Many More "
    Section 1: CNN's
    14 Lessons
    • What is Convolution
    • Examples of Filters
    • How do CNNs work
    • Difference between CNN's and ANN's
    • Transpose Convolutions
    • Applications of CNN's
    • Implementation of CNN's In TensorFlow
    • Implementation of CNN's in PyTorch
    • Implementation of CNN's in Keras
    • Popular CNN Architectures
    • Optimizing CNN's
    • Implementing Optimization Techniques in Keras
    • Optimizing CNN's in PyTorch
    • Quiz
  • Module - 6: RNN's
    Go Zero-One by learning the much-needed fundamentals of “RNN's". In this course, you will learn "Introduction to RNN's, Different Types of RNN's, Brief Introduction to GRU's and LSTM's and Many More "
    Section 1: RNN's
    6 Lessons
    • Introduction to RNN's
    • Different Types of RNN's
    • Brief Introduction to GRU's and LSTM's
    • Preprocessing of Sentences
    • Implementation of a Sequence Model in Keras
    • Quiz
  • Module - 7: GAN's
    Go Zero-One by learning the much-needed fundamentals of “Autoencoders and GAN's". In this course, you will learn " Introduction to Autoencoders, Autoencoders in PyTorch, Introduction to GAN's, GAN's in PyTorch "
    Section 1: Autoencoders and GAN's
    5 Lessons
    • Introduction to Autoencoders
    • Autoencoders in PyTorch
    • Introduction to GAN's
    • GAN's in PyTorch
    • Quiz
  • Certificate
    Once you've successfully completed the course, You will receive the certificate

Get Certified! Get Recognized…

Upon successful completion of the Course, You will receive a Verifiable certificate with QR code. Now employers can verify the certificates just by scanning QR code or by verification ID.

Differentiate yourself

The knowledge and skills you've gained working on projects, simulations, case studies will set you ahead of competition.

Share your achievement

Talk about it on Linkedin, Twitter, Facebook, boost your resume or frame it - tell your friends about it.

Learn

Learn in-demand technology skills through immersive content.

Practice

Practice the tech skills and build real-world projects for your portfolio.

Apply

Apply your knowledge in hackathons to grab internships and placements.

Assess

Assess your knowledge with quiz's, mock tests and interviews.

What our students say about SkillLauncher

Happy Students & Feedbacks

Ajeet Deshpande

Student

Great learning platform for all type of learners, New trending courses with new teaching methods, really good work. Thanks SkillLauncher!

Pravin Pratap Basu

Student

Support on the courses is very good. Apart from that course materials are also good . Teaching faculties are also extremly supportive.

Basanti Mahal

Student

The courses are very good and well structured. SkillLauncher even covered more advanced topics which was not in agenda or course content.

Anil Prasad

Student

These guys rock with amount of patience, knowledge and love how to explain things and cannot thank enough for the extreme support and mentoring.

Rama Krishna

Student

Content of courses is amazing. No other online platform has as many courses with dedicated teaching assistance. It has some free tutorials with time access.

Pirzada Gagrani

Student

I was searching for a platform to learn AI/ML course and I came across this SkillLauncher. Their support was awesome from the day of enrollment.

Sign in with Google