Certificate Program in

Artificial Intelligence and Machine Learning

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Herovired

Eligibility

Bachelor’s degree

Application deadline

To be announced

AIML

About this program

Case-based learning with 5+ mini projects tied into the program

Python, PyTorch, NumPy, Matplotlib, and Seaborn are the essential tools covered

7+ Industry projects and case studies

Overview
Curriculum
Certification
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Pricing
FAQ

Our recipe for your success

Batch starts

Coming Soon

Duration

11 months

Total effort

654+ hrs

Case-based learning with 5+ mini projects tied into the program

Python, PyTorch, NumPy, Matplotlib, and Seaborn are the essential tools covered

7+ Industry projects and case studies

Experience the difference with live learning

Real time engagement withlive classes

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Learn at your pace, on your schedule

Enhanced outcomes through more than 80% live and experiential learning

Our holistic learning philosophy

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Live learning

Live learning

Interactive classes with industry experts for hands-on learning

Case studies

Case studies

Real-world tasks to solidify knowledge and prep for industry challenges.

1:1 counselling

1:1 counselling

Personalized mentorship for career navigation and professional decisions.

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Seasoned faculty

Seasoned faculty

Guidance from leading industry experts to ensure top-tier learning.

Capstone projects

Capstone projects

Final projects that blend learning with real impact in your field.

Doubt clearing sessions

Doubt clearing sessions

Targeted sessions to ensure clarity and readiness for next steps.

Curriculum

Python Programming

    Installation and Set-upPython Basics - Syntactics,Variable Types, OperatorsFunctions - Built-in, Library and Custom, ArgumentsData Structures and Operations: Lists, TupleData Structures and Operations: DictionariesFor/While Loops, Conditional StatementsNested Loops and Nested ConditionsFile Handling - I/O functions, open() read, write, append , withHandling json and xml files and using csv module

    Doing version control on local sytem, branching, creating remote repository on github, working collaboratively on github, raising PR, merging PR

    Introduction to Pandas and Numpy ModulesPandas Basics - Data File Handling, Row/Columns Handling, Slicing, Drop, Sort, New Variable Creation, Observing Frequency CountPandas Advanced: Multiple Datasets Handling, Merge/Append, Multivariable Groupby/Crosstab SummariesWorking with Datetime Data and Time Series DataWorking with Indexes and Multi-level Indexing

    Importance of Visualizing Data through ChartsTypes of Charts and their Best UsesBasics of Visualization in Python Using Matplotlib and Seaborn:Components of a Plot, Subplots, Functionalities of a PlotPlotting Data Distributions,Univariate distributions

    Databases - Schema, Table, Relations.Basics of SQL, SQL commands - SELECT, FROM, WHERE, AND, OR, NOT, Pattern matching, sorting, Orderby, Comments and OperatorsGroup by, aggregate functions (MIN,MAX,SUM,AVERAGE,COUNT), having CRUD operations: Create and Drop Data bases, Create and Drop TablesConstraints (Primary key, Foreign Key, Unique key, Not Null, Default and CHECK)Joins (inner/left/right/full)Nested QueriesWindows Analytical Functions (Aggregate, Ranking, and Windows Analytical Functions)Speed up Queries Using IndexesIn this module, learners will explore the different frameworks to create the business model for the product.Various Types of Indexes

    Doing sanity checks on dataFinding relationship between continous variablesFinding relationship between categorical variablesFinding relationship between a categorical and continous variable

    Identifying scenarios where a binomial or a poisson distribution can be usedEnumerating the values that a random variable can takeComputing probability mass using binomial or poisson distribution

    Be able to formulate correct form of null and alternate hypothesis when underlying random variable is binomial or poissonBe able to arrive at the correct formulation of p-valueBe able to use CLT to tackle scenarios involving large sample means

    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 testsBe able to arrive at a business decision once the test has been done

    Undertand the idea of predictor variables and target variables.Outline how a trained model is to be validatedIdentify regression, classification and clustering tasks

    OLS Regression ModelPredicting continuous variableUsing Gradient Descent for Linear Regression, Model evaluation using loss functions, RMSE, R-Square, Stochastic Gradient Descent

    Predicting a binary variable, interpreting model output, using Python to create a logistic model – using statistics and machine learning methodsChecking model diagnosticsConcept of Confusion Matrix and Computing Accuracy Metrics, ROC, AUC, doing kfold cross validation

    Decision TreesChecking model diagnosticsBagging and Boosting TechniquesRandom ForestOOBHyperparameter tuning using GridSearch

    Introduction to clusteringDistance normsK-means clustering, Elbow method, Silhouette Score, Profiling

    Tfidf featurization and text classificationUsing spacy to handle classical tasks such as lemmatization, pos tagging, dependency parsingBuilding topic models and discovering key-terms

    Building a model training pipeline.Building model as an api service.

    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

    Building datasets and dataloadersDefining custom modelsUsing early stopping and logging Using different types of optimizers

    Word vectors and embedding layersSequential Processing using RNN and LSTM LayersAttention mechanism and encoder-decoder architecture Using hugging face to build bert based models
AIML

Unlock valuable insights

5-star rating by 97% of students.

Discover the outcomes of the program.

Explore the custom-curated learning path.

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Launch projects, leap forward

Environmental analysis

Environmental analysis

Examine environmental data, encompassing metrics such as air or water quality, to comprehend the influence of human activities on our surroundings and pinpoint areas requiring enhancement and mitigation efforts.

E-Commerce Website

E-Commerce Website

Interrogate data derived from e-commerce platforms, including sales trajectories, customer behavior patterns, and product popularity, with the objective of identifying potential avenues for refinement and optimization.

Financial analysis

Financial analysis

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

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In collaboration with

National Skill Development Corporation

NSDC has trained over 5.2 million students, leveraging a vast network of partnerships.

Participates in WorldSkills to showcase and enhance the international standards of Indian skills​.

Collaborates with global tech leaders like Google and Microsoft to advance digital skills training.

Hero Vired Certificate

Get certified

Leveraging Snapchat's expertise in pioneering augmented reality technologies and Unreal Engine's leadership in immersive virtual experiences, this certificate sets you apart in extended reality.

* Certificates are indicative and subject to change

Our faculty, your mentors

Soumita Mukherjee

Soumita Mukherjee

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Faculty, Hero Vired | 14+ years of corporate experience

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Soumita Mukherjee, a marketing and management expert with 15+ years in FMCG, has worked at Amazon, HUL, Pidilite, and Raymond. With an MBA from Goa Institute of Management and a Bachelor's from NIFT Mumbai, she's now a faculty at Hero Vired. Specializing in CRM, branding, product management, and go-to-market strategies, Soumita excels in category management, sales strategy, and driving successful brand growth through new product nurturing.

Education

MBA from Goa Institute of Management and a Bachelor's in Design from NIFT Mumbai

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Ben Campose

Ben Campose

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Director, Act Global Trainers India | 30+ years of experience

IBM

Ben has over 30 years of coaching experience in Sales, Leadership and professional development across industries.

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Start your learning journey, today

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Become an HV star with continued support beyond graduation

Certificate Program in

Artificial Intelligence and Machine Learning

Powered by

Herovired

EMI Starts at

₹3,565 / month

Price: ₹1,25,000 + GST

What you will get:

Case-based learning with 5+ mini projects tied into the program

Python, PyTorch, NumPy, Matplotlib, and Seaborn are the essential tools covered

7+ Industry projects and case studies

Duration

11 Months

Apply by

To be announced

0

Frequently Asked Questions

What is Artificial Intelligence and Machine Learning course all about?

An AI & ML course focuses on teaching you the different concepts and technologies associated with the field. An artificial intelligence and machine learning program will cover tools like Pandas, NumPy, Seaborn, Git, PyTorch, and more.

An artificial intelligence and machine learning program can help you develop skills and knowledge to stay relevant in the industry. It will prepare you for high-paying roles like computer vision engineer, AI engineer, machine learning engineer, and more.

The artificial intelligence and machine learning course will teach you to work with Python, Pandas, Git, NumPy, Seaborn and more to design technologies for the future. You will receive knowledge about different concepts like data visualization, SQL foundations, predictive modelling, and more.

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Hero Vired is a leading LearnTech company dedicated to offering cutting-edge programs in collaboration with top-tier global institutions. As part of the esteemed Hero Group, we are committed to revolutionizing the skill development landscape in India. Our programs, delivered by industry experts, are designed to empower professionals and students with the skills they need to thrive in today’s competitive job market.

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