Artificial Intelligence

Artificial Intelligence Foundations

This course will teach you the foundations of Supervised machine learning. Process of building and assessing a supervised machine learning model in a regression setting will be covered along with Clustering & its use cases, various preprocessing techniques with the help of hands-on exercises in Jupyter notebook and improving model performance while dealing with the issues with model complexity. Deep Learning concepts will be covered in detail with the dynamics behind the Neural Algorithms and building basic Neural Nets for problem-solving.

Verified Certificate

Guided Projects

24 hrs content from Top instructors

5+ Assignments & Quizzes

Discussion Support

Course Fee
₹ 8,000

₹ 3,999 incl. GST

Course Duration

24 Hrs

Prerequisite

  • Python
  • Statistics
  • Basic Mathematics

Your Faculty

Target Job Roles

  • The course helps you in gearing yourselves for the below-mentioned job roles which are in high demand and pay a good salary
  • Data Scientist
  • Deep Learning Engineer
  • Deep Learning Specialist
  • AI Engineer

Certificate

Earn a Verified Certificate from Great Learning Academy, which is highly regarded and valued by corporates. Make your CV & LinkedIn profile stand out from the rest.

Great Learning - Machine Learning Certificate

Curriculum

Module 1

Supervised Learning

Great Learning - Data Analytics using Excel Cerificate 6 hrs

  • Concepts of machine learning and Importance
  • Feature or Mathematical space
  • Supervised machine learning - Introduction
  • Linear regression and Pearson’s coefficient
  • Linear regression - Mathematical concept
  • Linear Regression - Advantages and Disadvantages
  • Descriptive analysis on the dataset
  • Analyse the Distribution - Dependent column
  • Missing Values imputation
  • Bivariate analysis - Seaborn
  • Building model using all information
  • Exploratory data Analysis(EDA)
  • Model Analysis and Squared errors
  • Fluke correlation
  • Logit function in Logistic regression
  • Probability examples and model predictions
  • Hands-on exercise on logistic regression
  • Introduction to Naive Bayes' Classifier
  • Naive Bayes' Classifier and examples
  • Naive Bayes' - Hands on
  • Show more

Module 2

Unsupervised learning

Great Learning - Data Analytics using Excel Cerificate 4 hrs

  • Unsupervised learning_Clustering
  • Clustering - Types and Distance
  • Clustering - Distance calculations
  • K-means Clustering
  • Elbow method
  • Visual analysis for Clustering
  • Hands on exercise - K-means clustering
  • Hierarchical Clustering
  • Measuring distance between clusters
  • Hands on exercise - Hierarchical clustering
  • Principal Component Analysis
  • Principal Component Co-variance Matrix
  • PCA for Dimensionality Reduction
  • Hands on exercise - PCA
  • Show more

Module 3

Introduction to Neural networks and Deep learning

Great Learning - Data Analytics using Excel Cerificate 7 hrs

  • Introduction to Neural Networks
  • Activation functions
  • Feed forward neural network
  • Back propagation and Gradient descent
  • Learning Rate setting and tuning
  • Hands-on Python Demo: Building a Neural Network from Scratch
  • Introduction to Tensorflow
  • Computational Graph
  • Hands-on in TensorFlow: Linear regression on Boston Housing prices
  • Introduction to Keras
  • Build a Deep Neural Network in Keras: MNIST Dataset
  • Feed forward
  • Back Propagation
  • Fully Connected Layer - Forward pass
  • Fully Connected Layer - Backward pass
  • Activation Functions
  • Softmax
  • Cross-Entropy Loss
  • Hands-on-Python-demo : MNIST walk-through of building blocks of Neural Networks
  • Show more

Module 4

Computer Vision

Great Learning - Data Analytics using Excel Cerificate 5 hrs

  • Working with Images_Introduction
  • Working with Images - Digitization, Sampling, and Quantization
  • Hands-on Python Demo: Working with images
  • Introduction to Convolutions
  • 2D convolutions for Images
  • Convolution - Forward and Backward
  • Transposed Convolution and Fully Connected Layer as a Convolution
  • Pooling : Max Pooling and Other pooling options
  • Hands-on Keras Demo: MNIST CNN Building Blocks code walk-through
  • CNN Architectures and LeNet Case Study
  • Case Study : AlexNet, ZFNet, VGGNet, GoogleNet, ResNet
  • GPU vs CPU
  • Transfer Learning Principles and Practice
  • Hands-on Keras Demo: SVHN Transfer learning
  • Show more

Module 5

Natural Language Processing

Great Learning - Data Analytics using Excel Cerificate 2.5 hrs

  • Introduction to NLP
  • Pre-processing in NLP-Tokenization, Stop words, Normalisation,stemming and lemmatization
  • Pre-processing in NLP-Bag of words, TF-IDF as features
  • Language Models Probabilistic models, N-gram model and channel model
  • Hands-on demo_NLP Basics with NLTK
  • Word2Vectors
  • Glove
  • Hands-on demo : Word Embeddings
  • Applications : POS tagging, NER
  • Hands-on demo : POS tagging with NLTK
  • Hands-on demo : TF-IDF with NLTK
  • Show more

FAQs

For how long can I access these courses?

You can access all these courses for 1 year.

Is it 100% online learning and self-paced?

It is a 100% online learning course that you can learn at your own pace through our website and mobile app.

On what basis are the certificates rolled out?

The certificates are rolled out as and when you complete the mandatory course content and submit the project with a satisfactory grade.

Will I gain access to any sort of Forum support?

Yes. You will gain complete access to our Discussion forum support in your course to connect with our SMEs to resolve your course content related queries within 48 hrs.

Is there a refund in case I want to discontinue from the course?

Fees once paid is not refundable. Kindly make an informed decision before enrolling into the course.