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Programs

Placement Assurance

Accelerator Program in

Artificial Intelligence and Machine Learning

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Placement Assurance with a minimum of 8-10 job opportunities
Case-based learning with 5+ mini projects tied into the program
Python, PyTorch, NumPy, Matplotlib, and Seaborn are the essential tools covered
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Learners

Artificial Intelligence and Machine Learning

Learners Success & Placement

10,000+ AL & ML jobs in India. You can   be one of them

Can Will

10,000+ AL & ML jobs in India. You can be one of them

Can Will
Our Learner Success Team will ensure to get you the right skills you need to become a
Data Scientist
3787+ Jobs
Machine Learning Specialist
1562+ Jobs
Machine Learning Engineer
2478+ Jobs
AI Engineer
2435+ Jobs
Computer Vision Engineer
1316+ Jobs
NLP Engineer
1644+ Jobs
Data sourced from Linkedin
Average salary range
Briefcase
5 Lakhs - 22 Lakhs
17 June 2023
Next Cohort Starts
11 Months
Duration
Bachelor’s degree
Eligibility
Bachelor's Degree in a technology-related discipline/ STEM back ground with mandatory python coding knowledge. Familiarity with introductory calculus and linear algebra
31 March 2023
Application Deadline
Bachelor's Degree in a technology-related discipline/ STEM back ground with mandatory python coding knowledge. Familiarity with introductory calculus and linear algebra
Curriculum

Custom curated international curriculum

The program explores the concepts and techniques of Artificial Intelligence and Machine Learning. Learn to work with Python, NumPy, Pandas, Git, PyTorch, etc. to develop future-ready technology.
Live Online Duration
222
Hours
Total Effort Required
654
Hours
Total Weekly Effort
14
Hours

Tools Covered

Pandas
Python
PyTorch

Syllabus

Program Brochure

For detailed curriculum and program structure, download the program brochure

Download Brochure
Python Programming
  • Installation and Set-up
  • Python Basics - Syntactics, Variable Types, Operators
  • Functions - Built-in, Library and Custom, Arguments
  • Data Structures and Operations: Lists, Tuple
  • Data Structures and Operations: Dictionaries
  • For/While Loops, Conditional Statements
  • Nested Loops and Nested Conditions
  • File Handling - I/O functions, open() read, write, append , with
  • Handling json and xml files and using csv module
  • Object Oriented Approach to Programming
Git and Version Control
Doing version control on local sytem, branching, creating remote repository on github, working collaboratively on github, raising PR, merging PR
Data Analysis using Pandas & Numpy
  • Introduction to Pandas and Numpy Modules
  • Pandas Basics - Data File Handling, Row/Columns Handling, Slicing, Drop, Sort, New Variable Creation, Observing Frequency Count
  • Pandas Advanced: Multiple Datasets Handling, Merge/Append, Multivariable Groupby/Crosstab Summaries
  • Working with Datetime Data and Time Series Data
  • Working with Indexes and Multi-level Indexing
Data Visualization
  • Importance of Visualizing Data through Charts
  • Types of Charts and their Best Uses
  • Basics of Visualization in Python Using Matplotlib and Seaborn:
  • Components of a Plot, Subplots, Functionalities of a Plot
  • Plotting Data Distributions,Univariate distributions
SQL Foundations
  • Databases - Schema, Table, Relations
  • Install SQLITE
  • Basics of SQL, SQL commands - SELECT, FROM, WHERE, AND, OR, NOT, Pattern matching, sorting, Orderby, Comments and Operators
  • Group by, aggregate functions (MIN,MAX,SUM,AVERAGE,COUNT), having
  • CRUD operations: Create and Drop Databases, Create and Drop Tables
  • Constraints (Primary key, Foreign Key, Unique key, Not Null, Default and CHECK)
  • Joins (inner/left/right/full)
  • Nested Queries
  • Windows Analytical Functions (Aggregate, Ranking, and Windows Analytical Functions),
  • Speed up Queries Using Indexes
  • Various Types of Indexes
EDA
  • Doing sanity checks on data
  • Finding relationship between continous variables
  • Finding relationship between categorical variables
  • Finding relationship between a categorical and continous variable
Prob Dist: Binomial, Poisson
  • Identifying scenarios where a binomial or a poisson distribution can be used
  • Enumerating the values that a random variable can take
  • Computing probability mass using binomial or poisson distribution
Intro to Hypothesis testing
  • Be able to formulate correct form of null and alternate hypothesis when underlying random variable is binomial or poisson
  • Be able to arrive at the correct formulation of p-value
  • Be able to use CLT to tackle scenarios involving large sample means
ANOVA
  • Be able to correctly identify where to use ANOVA, 2 sample t test or chi square test of factor association
  • Be able to formulate correct null and alternate hypothesis for each of the tests
  • Be able to arrive at a business decision once the test has been done
Predictive Modelling Overview
  • Undertand the idea of predictor variables and target variables
  • Outline how a trained model is to be validated
  • Identify regression, classification and clustering tasks
Linear Regression
Linear Regression
  • OLS Regression Model –
  • Predicting continuous variable
  • Using Gradient Descent for Linear Regression, Model evaluation using loss functions, RMSE, R-Square, Stochastic Gradient Descent,
Logistic Regression
Logistic Regression:
  • Predicting a binary variable, interpreting model output, using Python to create a logistic model – using statistics and machine learning methods
  • Checking model diagnostics
  • Concept of Confusion Matrix and Computing Accuracy Metrics, ROC, AUC, doing kfold cross validation
Tree Based Ensembles
Tree based Ensembles:
  • Decision Trees
  • Bagging and Boosting Techniques
  • Random Forest
  • OOB
  • Hyperparameter tuning using GridSearch
K-Means Clustering
Clustering:
  • Introduction to clustering
  • Distance norms
  • K-means clustering, Elbow method, Silhouette Score, Profiling
Classical NLP
  • Tfidf featurization and text classification
  • Using spacy to handle classical tasks such as lemmatization, pos tagging, dependency parsing
  • Building topic models and discovering key-terms
Deploying Models and Creating a model pipeline
  • Building a model training pipeline.
  • Building model as an api service.
Introduction to Deep Learning
Introduction to Neural Networks: Introduction to Neuron, Activation functions - sigmoid, tanh, relu, etc Loss functions - cross-entropy loss, MSE, etc Optimization Techniques - Gradient Descent, Batch Gradient, Mini-batch Gradient and Stochastic Gradient etc. Building simple MLP using numpy
Deep Learning using Pytorch
  • Building datasets and dataloaders
  • Defining custom models
  • Using early stopping and logging
  • Using different types of optimizers
Deep Learning for Image Recognition and Object Detection
  • CNNs as feature extractors
  • Resnets and features extraction for Transfer Learning
  • Building single shot and multistage object detectors
Deep learning for NLP Tasks
  • Word vectors and embedding layers
  • Sequential Processing using RNN and LSTM Layers
  • Attention mechanism and encoder-decoder architecture
  • Using hugging face to build bert based models
AND
Why Hero Vired?

Get the Hero Vired Advantage

Hero Group
70-90% live interactive
classes
100% program completion rate
Personalized placement assistance
Small batch sizes for
focused teaching
Others
Pre - recorded
lectures
Low completion rate
No personalized
placement support
No limit on batch sizes
Faculty

Industry Leading Faculty

Learn from world-class faculty that will guide you through this certification program
Abhaya Agrawal

Abhaya Agrawal

MCA, Computer Science | 17+ years of experience

Seasoned professional with vast experience in Data Modeling, Solaris, LINUX, Python, Machine Learning, Cloud Computing, and Deep Learning
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Kartik Mudaliar

Kartik Mudaliar

MS, Computer Science | 7+ years of experience

Corporate trainer with Industry leading organizations in Data Science, Python and Databases. Specializes in Artificial Intelligence, Python, and Machine Learning.
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Infosys
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Shilpi Taneja

Shilpi Taneja

MCA, Computer Science | 15+ years of experience

Seasoned professional with hands on experience in Data Science, Data Analytics, and Data Mining. Has worked in academia for over 10 years.
HCL
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Rupal Bhargava

Rupal Bhargava

Ph.D. Computer Science | 7+ years of experience

She has a vast experience of research and mentoring. Broadly, her research interests lie at the intersection of Natural Language Processing and Machine Learning.
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Manoj Agarwal

Manoj Agarwal

Ph.D. Computer Science | 17+ years of experience

An expert in designing solutions using machine learning techniques. Specializes in multi-objective optimization techniques and evolutionary computations.
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Gunnvant Singh Saini (1)

Gunnvant Singh Saini

B.S. in Economics | 10+ years of experience

Specializes in Data Analysis, Creating Scalable Data Services, and Technical Curriculum Design. Has trained several professionals in India and abroad.
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Program Partners

Partnered with leading universities and organizations

Nsdc
Integrated withNational Skill Development Corporation
National Skill Development Corporation (NSDC) is a not-for-profit public limited company which provides funding to build scalable and profitable vocational training initiatives. The NSDC facilitates initiatives that can potentially have a multiplier effect as opposed to being an actual operator in this space. In doing so, it strives to involve the industry in all aspects of skill development.
Projects

Experience a holistic learning path

Get a hands-on learning experience by working on real-world projects from the most innovative businesses across the world. Take a sneak peek at some of our sample projects.
Lms E College
Environmental analysis

Analyze environmental data, such as air or water quality measurements, to understand the impact of human activities on the environment and identify areas for improvement

E Commerce Website
E-commerce analysis

Analyze data from an e-commerce website, such as sales trends, customer behavior, and product popularity, to identify areas for improvement and optimization

Financial analysis

Analyze financial data, such as stock prices and investment portfolios, to identify trends and patterns that can inform investment decisions.

Sports analytics

Analyze sports data, such as game scores, player statistics, and team performance, to identify patterns and insights that can be used to improve performance.

Public health analysis

Analyze public health data to understand trends and patterns related to a particular disease or health issue, such as COVID-19 or obesity rates.

Social media analysis

Collect and analyze data from social media platforms, such as Twitter or Instagram, to understand trends and sentiment related to a specific topic or brand.

Marketing analysis

Analyze a company's marketing strategy and performance by collecting and analyzing data on customer behavior, sales trends, and advertising campaigns.

Certificates

Get certified after you graduate from the program

Upon successful completion of this Artificial Intelligence and Machine Learning program, you will receive the following:

Hero Vired Certificate

Benefit from the Hero Group’s decades of research and understanding of the Indian education and job landscape. Get a certification accredited by National Skill Development Council and Media & Entertainment Skills Council.

* Certificates are indicative and subject to change

Personalized placement services to help you with your career goals
Motivation
1:1 career coaching
In Time
Just-in-time interview preparation
Selection
Guaranteed job opportunities
Enrollment

Application process

A simple yet thorough application process that will help you learn key skills to supercharge your career
Step 1
Submit application
Fill the form, review it, and submit your application. A fully completed application helps us assess your learning goals and enrol you into the program.
Step 2
Receive the offer letter
You will receive an offer letter to enrol, along with the complete details of the program, fee and payment schedule, etc.
Step 3
Block your seat
Pay a nominal amount to confirm your acceptance and block your seat.
*This is subject to any defined individual program eligibility, criteria and test that may be included as part of the enrolment process.
Program Pricing

Upskill yourself with Hero Vired

Live
70% to 90% Live Instructor-led Classes
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Gamified & Interactive Learning
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Discussion Forums and Community
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Industry Projects & Case Studies
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Practical Hands-on Learning Sessions
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Career Assistance and Workshops
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Personalized Placement Assistance
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Artificial Intelligence and Machine Learning
Part-time
Starting at
7,545/ month
Price: ₹3,00,000 + GST
Start Application
Application Deadline: 31 March 2023
Apply early to secure your seat
For queries, feedback & assistance
Reach out to us at
   1800 309 3939
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