- Introduction to Machine Learning
- Overview of Deep Learning and Artificial Intelligence
- ML Applications and Real-world problem examples (How is it happening in the companies, Why so much hype, Why companies want it, How is it everywhere)
- Future Scope and Jobs in Artificial Intelligence
- Industry Views over Jobs and its Future Scope
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- Artificial Intelligence and Machine Learning with Certification
Learning Path in AI and Machine Learning Course with Placement
Master the fundamentals of artificial intelligence and machine learning, such as natural language processing, deep learning, and computer vision.
Online
16 Weeks
₹ 125,000 150,000
Quick facts
particular | details | |
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Course overview
Artificial Intelligence and Machine Learning with Certification online courses are created by Board Infinity, an e-learning platform designed for learners to assist them in accomplishing goals to achieve their professional goals. Artificial Intelligence and Machine Learning with Certification online classes by Board Infinity are designed for individuals who want guidance directly from industry experts and to enhance their practical understanding to become certified AI and ML specialists.
Artificial Intelligence and Machine Learning with Certification online course involve more than 150 hours of thorough video lectures backed by hands-on assignments, projects, and case studies in this course. This course aims to give students a thorough understanding of both basic and advanced artificial intelligence and machine learning topics and approaches, such as deep learning, computer vision, natural language processing, generative algorithms, and convolutional neural networks. Applicants will have established experience in a variety of machine learning and artificial intelligence tools, including Power BI, Seaborn, Numpy, Pandas, Keras, Python, Maplplotlib, and Tensorflow, by the end of this course.
The highlights
- Certificate of completion
- Live online course
- 150 hours of video content
- Case studies
- Assignments
- Projects
Program offerings
- Online course
- 1:1 mentoring
- Learning resources. placement support
- Accessible on mobile devices
Course and certificate fees
Fees information
certificate availability
certificate providing authority
What you will learn
After completing the Artificial Intelligence and Machine Learning with Certification online training, applicants will develop an in-depth knowledge of both basic and advanced artificial intelligence and machine learning principles. The principles of deep learning, computer vision, and natural language processing will be explored by applicants. Applicants will gain knowledge of generative algorithms and neural networks, such as convolutional neural networks. Applicants will also gain a thorough understanding of the abilities required to work with artificial intelligence and machine learning tools such as Python, Pandas, Numpy, Tensorflow, Matplotlib, Keras, and Power BI.
Who it is for
The syllabus
Week 1: Introduction to Machine Learning and Artificial Intelligence
Week 1: Foundations on Python
- Getting started with Jupyter Notebook & Google Colab
- Python Basics
- Lists, Tuples, and Dictionaries
- OOPs Terminology
Week 2: Deep Learning and Introduction to Tensorflow
- Introduction to Deep learning
- Artificial neural network
- Gradient Descent and variants
- Backpropagation
- Introduction to Tensorflow and Keras
- A first artificial neural network with Sequential API
Week 3-4: CNN Foundations
- Introduction to CNN, convolutions, and pooling
- CNN parameters discussion
- Optimizers
- Functional API
- Writing first CNN on MNIST
- Advanced CNN concepts
- Types of Convolutions
- Discussion about Receptive Field
- Learning Rate Scheduler
- Regularization techniques
- Discussion about VGG, Inception, Resnet, Densenet architectures
- CNN training techniques
- Network Visualization Techniques discussion
- LR finder, Cyclic Learning rate, Progressive Resizing, Test Time Augmentation
- Intro to Transfer Learning and applications
- Differential Learning rate
- How to create a dataset from online
Week 5-6: Advanced Computer Vision
- Object Detection
- Introduction to Object detection
- Two-stage detectors and one-stage detector
- Faster-RCNN, YOLO, SSD
- Bounding box Annotation tool
- Training object detector
- Focal loss discussion
- Introduction to Image Segmentation
- FCN, UNet, Deeplab-V3
Week 6-7: Generative Algorithms
- Introduction to Generative Algorithms
- Autoencoder, Variational Autoencoder, and GAN
- DCGAN discussion
- Introduction to different GAN architectures
- Different Loss Functions for GAN’s
Week 7-8: Deployment on Cloud and Edge
- Introduction to tflite/tfjs
- Quantization and Model Compression
- Mobilenet and squeeze net
Week 8-9: Mathematics for Machine Learning, EDA
- Introduction to calculus
- Introduction to Linear Algebra
- Numpy
- Pandas - Cleaning and Munging Data - Visualizing Data
Week 9-11: Machine Learning(Supervised)
- Linear Models: Linear and Logistic Regression with Stochastic Gradient Descent
- Lasso, Ridge regression
- Probability-Based Models: Naive Bayes
- Tree-Based Model: Decision Tree and Random Forest - Ensemble Methods: Bagging, Boosting - Proximity Based Models: K Nearest neighbor - Model selection
Week 11-12: Machine Learning(Unsupervised)
- Clustering
- K-Means
- Hierarchical
- PCA
- Hyper Parameter Tuning
Week 12-13: NLP with Machine Learning
- Introduction to NLP
- Bag of words, tf-idf
- Sentiment analysis
- POS Tagging
- Named Entity Recognition
Week 13-14: NLP with Deep Learning
- Deep Learning in NLP
- Introduction to RNN, LSTM
- Word2vec
- Language models
Week 15: Advanced NLP
- Transformer Architecture
- Transfer Learning in NLP
- Introduction to BERT
- Variants of BERT
- Introduction to Hugging Face Library
Week 16: Career Services and Placement Preparation
- Self Awareness
- Industry Guidelines
- LinkedIn Profile Building
- How to become Kaggle Grand Master
- Build your GitHub profile
- Resume Building
- Role Clarity
- Life Skill Development
- How to search for a Job?
- Interview Cracking Techniques
- Salary Negotiation
Instructors
Mr Ruble Joseph
Vice President
eClerx
B.E /B.Tech
Mr Mirza Rahim Baig
Lead of Business Analytics
Flipkart Pvt. Ltd.
Mr Kunaal Naik
Marketing Operation Advisor
Freelancer
B.E /B.Tech
Mr Punit Shah
Data Science Lead
Freelancer
Other Bachelors, Other Masters
Mr Anil Chandra Naidu Matcha
Co Founder
Freelancer
B.E /B.Tech
Ms Geetanjali Prasad
Head Data science
Freelancer
B.E /B.Tech
Mr Rishi Raghuvanshi
Senior Data Scientist
Freelancer
B.E /B.Tech, M.E /M.Tech.
Mr Dhiman Mandal
Data Scientist
Ericsson
B.E /B.Tech, M.E /M.Tech.
Mr Pulkit Aneja
Data Scientist
Amazon
Mr Vedant Dwivedi
Deputy Manager
Reliance Jio Infocom...
Mr Kishan Kanhaiya
Data Scientist
Freelancer
B.E /B.Tech
Mr Anurag Mukherjee
Senior Analyst
Accenture
B.E /B.Tech
Mr Ravi Teja
Co-Founder
Freelancer
B.E /B.Tech
Mr Rajanikant Ghate
Data Scientist
Freelancer
B.E /B.Tech, M.E /M.Tech.
Mr Abhishek Dubey
Data Scientist
Freelancer
Other Masters