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Artificial Intelligence Course in Thane

82,124 Ratings

This artificial intelligence course in Thane by IITM Pravartak and Intellipaat is curated by AI experts. They will make you a certified professional in AI by teaching you PySpark, Tableau, Git, etc. Get the best artificial intelligence training in Thane to master this domain and get certified.

Ranked #1 Artificial Intelligence Course by India TV

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AI Course Key Highlights

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Madras Faculty and Industry Practitioners
1:1 with Industry Mentors
Resume Preparation and LinkedIn Profile Review
24*7 Support
No-cost EMI Option
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Artificial Intelligence Course in Thane Overview

What modules will be covered by this best Artificial Intelligence course?

Through this AI training course in Thane, you will be able to learn the following concepts:

  • Data visualization with Tableau
  • Microsoft Excel for data analysis and data transformation
  • Techniques of evaluation, experimentation, and project deployment
  • Natural Language Processing (NLP) and its applications
  • Data science projects, analytics, and recommender systems
  • Python with data science
  • Machine learning algorithms
  • Git, Storytelling
  • Data science at scale with PySpark, AI with TensorFlow
  • Data analysis, project life cycle, and data science in the real world
  • Analysis segmentation using clustering and the technique of prediction
  • Deploying machine learning models on Clouds (MLOps)

Some of the reasons for you to sign up for artificial intelligence courses in Thane are as follows:

Reason Source
The average salary range for AI professionals in Thane, Maharashtra, is from ₹465,200 to ₹762,100 per annum. Indeed
There are over 2,000 job openings for AI professionals in Maharashtra. LinkedIn
Major companies like PayPal, JP Morgan, Amazon, and others are actively hiring AI professionals in India. Glassdoor

To enroll in one of the leading AI courses in Thane, there are no specific skills required. Register today!

Listed below are the professionals who are eligible to enroll in this artificial intelligence certification course in Thane:

  • Data scientists
  • Analysts
  • Search engine professionals
  • E-commerce experts
  • Software professionals
  • Those aiming to start a career in Artificial Intelligence and Machine Learning
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Artificial Intelligence would be the ultimate version of Google - Larry Page
The global Artificial Intelligence market size is expected to grow at a compound annual growth rate (CAGR) of 42.2% from 2020 to 2027 - Grand View Research

Career Transition

57% Average Salary Hike

$1,14,000 Highest Salary

12000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Artificial Intelligence Mentors

Skills Covered

Python

Data Science

Data Analysis

AI

Git

MLOps

Data Wrangling

SQL

Storytelling

Machine Learning

Prediction Algorithms

NLP

PySpark

Model

Data Visualization

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Tools Covered

pyspark python jupyter Scipy numpy pandas matplotlib tensorflow SQL tableau excel git SparkSQL
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Artificial Intelligence Course Fees in Thane

Online Classroom Preferred

  • Everything in Self-Paced Learning, plus
  • 50+ Live sessions across 7 months of Instructor-led Training
  • One to one doubt resolution sessions
  • Attend as many batches as you want for Lifetime
  • Job Assistance
30 Mar

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

20 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

18 May

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$1,229 10% OFF Expires in

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  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Artificial Intelligence Course Syllabus

Live Course Industry Expert Academic Faculty

Module 1 – Preparatory Session - Linux and Python

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Python 

  • Introduction to Python and IDEs – The basics of the Python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling, etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 
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Module 2 – Data Wrangling with SQL

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SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables 

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table. 
  • Stored procedures, rank function, SQL ROLLUP, etc.

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc. 
  • Clustered indexes, common table expressions.

Hands-on exercise: 

Writing comparison data between the past year and the present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

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Extract Transform Load

  • Web Scraping, Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.

Data Manipulation Using Pandas

  • Loading the data, data frames, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross-validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib.
  • Regression plots, categorical plots, area plots, etc, with Python seaborn.
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Descriptive Statistics – 

  • Measure of central tendency, the measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, Bayes’ theorem, central limit theorem. 

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.
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Introduction to Machine Learning 

  • Supervised, Unsupervised Learning.
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.

Classification 

  • Introduction to classification problems, Identification of a classification problem, and dependent and independent variables.
  • How to train the model in a classification problem.
  • How to evaluate the model for a classification problem.
  • How to optimize the efficiency of the classification model.

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  • How to train the model in a clustering problem.
  • How to evaluate the model for a clustering problem.
  • How to optimize the efficiency of the clustering model.
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Supervised Learning 

  • Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree – Creating decision tree models on classification problems in a tree like format with optimal solutions.
  • Random Forest – Creating random forest models for classification problems in a supervised learning approach.
  • Support Vector Machine – SVM or support vector machines for regression and classification problems.
  • Gradient Descent – Gradient descent algorithm that is an iterative optimization approach to finding the local minimum and maximum of a given function.
  • K-Nearest Neighbors – A simple algorithm that can be used for classification problems.
  • Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.

Unsupervised Learning 

  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  • Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data.
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  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model.
  • r2, adjusted r2, mean squared error, etc.
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Artificial Intelligence Basics 

  • Introduction to keras API and TensorFlow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning

  • Introduction to Deep Learning (by Academic Faculty)
  • Deep neural networks
  • Convolutional Neural Networks 
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted boltzmann machine 
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The Data Science capstone project focuses on establishing a stronghold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals:

  • Extracting, loading and transforming data into usable format to gather insights.
  • Data manipulation and handling to pre-process the data.
  • Feature engineering and scaling the data for various problem statements.
  • Model selection and model building on various classification, and regression problems using supervised/unsupervised machine learning algorithms.
  • Assessment and monitoring of the model created using the machine learning models.
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Electives:

Power BI Basics

  • Introduction to PowerBI, Use cases and BI Tools, Data Warehousing, Power BI components, Power BI Desktop, workflows and reports, Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data,M Query and Hierarchies in Power BI.

DAX 

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics  

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data.

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  • Job Search Strategy
  • Resume Building
  • Linkedin Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.
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Artificial Intelligence Course Assignments and Projects

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends — the possibilities are endless and our community has something for everyone!

class-notifications
Hackathons
career-services
major-announcements
collaborative-learning

Career Services

Career Services

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions that will help you stay on track with your upskilling.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through several mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing the Placement Readiness Test (PRT)

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Artificial Intelligence Certification in Thane

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This artificial intelligence course in Thane is developed by leading AI professionals to help you find the best AI Engineer jobs at top MNCs. During this training program, you will work on real-world projects that will evaluate your skills and learn to deal with real-time business scenarios. Thus, they will help you accelerate your career effortlessly.

At the end of this artificial intelligence online course, there will be quizzes that reflect the type of questions asked in the certification exam, and they will help you score better.

After this training, you will receive certification from Intellipaat and CCE, IIT Madras. Once you complete the project work (after its review) and score at least 60% on the quiz. This AI training in Thane is well-recognized by the top 80+ organizations, such as Cognizant, Ericsson, Mu Sigma, Hexaware, Saint-Gobain, Standard Chartered, Cisco, Sony, Genpact, TCS, etc.

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Artificial Intelligence Course in Thane FAQs

Can Intellipaat provide the artificial intelligence course near me in Thane?

This AI course offered by Intellipaat is an online training program, so you have the option to attend it from any locality in Thane. Be it Vasant Vihar, Hiranandani Estate, Panch Pakhdi, Vrindavan Society, Shrirang Society, Khopat, Kolbad, Louis Wadi, Majiwada, Lokmanya Nagar, Ghodbunder Rd, or anywhere else. You can attend Intellipaat’s advanced artificial intelligence classes from your home or office.

Intellipaat is the leading provider of AI courses in Thane. Courses such as machine learning, data science, R programming language, and others help you become job-ready by focusing on the practical implementation of the concepts in real-time live projects.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have successfully completed the training and moved to the placement pool after clearing the PRT( Placement Readiness Test) More than 500+ top MNC’s and startups hire Intellipaat learners. Our Alumni works with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Apparently, no. Our job assistance is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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