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ML & AI Kickstart

Welcome to the ML & AI Kickstart Course — your entry point into the revolutionary world of Machine Learning (ML) and Artificial Intelligence (AI). Designed for aspiring data scientists, software developers, and AI enthusiasts, this course offers a comprehensive journey from core fundamentals to real-world applications.

Enrolled:3

Last Updated:04/07/2025

22 LPA

Average Package

120%

Salary Hike

83 LPA

Highest Package

What I will learn?

Material Includes

7+ Live Classes & Recordings

24/7 Live Doubt Support

Practice Questions

Topic wise Quizzes

Case Studies

Access to Global Peer Community

Cartificate of Completion

Referrals

About Course

Welcome to our comprehensive Data Structures and Algorithms (DSA) course! If you’re eager to strengthen your problem-solving skills and excel in coding interviews, you’ve come to the right place.

Our course is meticulously designed to provide you with the essential skills and knowledge needed to tackle real-world coding challenges with confidence.

Course Curriculum

Introduction to the ML & AI Kickstart
A brief introduction to what's coming ahead, and how you can make the most out of it. In this module, we answer some very basic yet crucial questions to lay the foundations of the journey we are going to begin. Excited to have you onboard!!!

What is Machine Learning?

00:00
How exactly does Machine Learning work?

00:00

The Python Programming Language
Before starting with ML, let's first have a look at the programming language we'll be using. In this module, we'll dive into Python programming essentials tailored for Machine Learning. Expect to cover basic syntax, essential data structures, functions and modules. By the end, you'll be equipped with the foundational skills necessary to start programming in Python.

Numpy

Pandas
Pandas is a widely used Python library for data manipulation and analysis. It provides high-level data structures and functions designed to make working with structured data fast, easy, and expressive. This note serves as an introduction to Pandas, covering its key features, data structures, and common operations.

Data Visualisation
Data visualization is the graphical representation of data and information. It plays a crucial role in machine learning (ML) and data science by aiding in the understanding, interpretation, and communication of complex datasets. The primary objectives of data visualization in these fields are to explore, analyze, and present insights from data to facilitate informed decision-making.

Probability Distribution and Statistics
Probability distribution and statistics are fundamental concepts in the field of mathematics and are extensively used in various disciplines, including but not limited to, economics, engineering, social sciences, and natural sciences.

Linear Regression
Linear regression is a fundamental statistical method used in machine learning to model the relationship between a dependent variable and one or more independent variables. This technique aims to find the best-fit line that minimizes the difference between the observed data points and the predicted values. Linear regression is widely used for predictive analysis, trend forecasting, and determining the strength of predictors. In this lesson, we will explore the basics of linear regression, including its assumptions, the least squares method for fitting a model, and evaluating model performance using key metrics. Understanding linear regression is essential as it forms the basis for more complex regression techniques and serves as a foundational tool in data analysis and machine learning.

Data Preprocessing
Data preprocessing is an important step in the data mining process. It refers to the cleaning, transforming, and integrating of data in order to make it ready for analysis. The goal of data preprocessing is to improve the quality of the data and to make it more suitable for the specific data mining task.

Decision Trees and Random Forests
Decision trees are intuitive and powerful tools for both classification and regression tasks in machine learning. They work by splitting the data into subsets based on feature values, creating a tree-like model of decisions. Each node represents a feature, each branch represents a decision rule, and each leaf node represents an outcome. This method is highly interpretable and easy to visualize, making it popular for understanding complex data. Random forests, on the other hand, are an ensemble learning method that enhances the predictive performance of decision trees. By constructing a multitude of decision trees during training and outputting the mode or mean prediction of the individual trees, random forests reduce the risk of overfitting and improve accuracy. This technique leverages the power of multiple trees to achieve robust and reliable predictions. In this module, we will explore the construction, advantages, and practical applications of both decision trees and random forests, highlighting their role in solving real-world machine learning problems.

Gradient Boost Models
In this module, we take a look at gradient boosting models and fine-tuning model hyperparameters using Optuna, GridSearch CV and RandomSearchCV.

Hyperparameter Tuning

Introduction to Deep Learning
Deep learning is a subset of machine learning based on artificial neural networks, inspired by the structure and function of the brain. It focuses on training models, known as deep neural networks, which consist of multiple layers of interconnected nodes or neurons, to automatically learn hierarchical representations of data.

Neural Networks
Neural Networks are computational models that mimic the complex functions of the human brain. The neural networks consist of interconnected nodes or neurons that process and learn from data, enabling tasks such as pattern recognition and decision making in machine learning. The article explores more about neural networks, their working, architecture and more.

Classification Measures
Classification is a fundamental task in machine learning (ML), involving the categorization of data into predefined classes or categories based on input features. Accurately evaluating the performance of classification models is essential for assessing their effectiveness in real world applications. This module provides a detailed examination of various classification measures used in ML.

Project Delivery

Deployment

Student Ratings & Reviews

No Review Yet

No Review Yet

Our Instructors

Daily schedule

Live, hands-on, activity-led sessions conducted by the instructor

Mon-Sat, 09:00 PM – 10:00 PM (IST)

What You Will Get Post Completion Of Your Program

Referrals

Enhance your job search with strong industry referrals, connecting you to exclusive opportunities at top tech companies.

Home Course ML & AI Kickstart

ML & AI Kickstart

Welcome to the ML & AI Kickstart Course — your entry point into the revolutionary world of Machine Learning (ML) and Artificial Intelligence (AI). Designed for aspiring data scientists, software developers, and AI enthusiasts, this course offers a comprehensive journey from core fundamentals to real-world applications.

Enrolled:3

Last Updated:04/07/2025

Enrollment validity: Lifetime

Total Enrolled

3
Duration

200 hours
Certificate

Certificate of completion

We have helped build 1000+ Careers

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Boost Your Career with a Course Completion Certificate

Earning a course completion certificate enhances your resume, demonstrating your commitment to learning and skill development. It increases your chances of getting hired by showcasing your expertise to employers. A certified qualification can set you apart from other candidates, improve your credibility, and open new job opportunities in your field.

What Our Students Are Saying

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How Soma Shaker Cracked Amazon SDE Interview with 150% Hike | Get SDE Ready Review

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Student Feedback | Pranay on Our Mastering DSA Instructor Class

Frequently Asked Questions

Easily find answers to common questions about our courses and services

Who should join this course?

Our courses are intended for anyone aspiring to become a Software Development Engineer. This includes university students who have very basic programming knowledge (2nd year or above), working professionals looking for a career switch or trying to upskill themselves, and anyone interested in the field of software development.

Is the amount refundable if I don't like the course?

This course offers a no-questions-asked, full refund policy effective within seven days of its registration.

What is the mode of the course, online or offline?

The course is 100% online. All the classes are going to be 100% live.

What if I miss a class?

You will be getting recordings of your classes and you will have lifetime access to them.

Are there any prerequisites?

Only basic programming knowledge is required.

Will there be doubt classes?

We have 24/7 live doubt support. Also, we conduct live doubt classes regularly as well in the weekdays whose timings are from 9pm-11pm.

Is placement guaranteed after completing the course?

Yes, we offer guaranteed placement upon successful completion of the course, including all required assessments and tests. Our program is structured to ensure you’re job-ready through rigorous training, real-world projects, and interview-focused preparation. Clearing the internal tests is a key part of the process to validate your readiness for placement opportunities.

What is the duration of the course?

The course’s duration is 3 months, though it can be extended if there is a need for additional classes focused on specific topics or further doubt sessions.

I have a full time job. Not sure if I will be able to make it?

The course is for working professional only. That’s why the timings are such: Instructor classes are on the weekends from 12pm-3pm. Doubt Classes are on the weekdays from 9pm-11pm.

Would there be any certificate on completion?

Yes! you will be getting certificate of completion.

Do you provide placement assistance?

Yes we provide placement assistance.

Its in 4 steps:

We will help you create a strong resume that increases your chances of getting shortlisted by companies.
⁠We will optimise your LinkedIn profile to ensure that recruiters can easily find and connect with you.
We will conduct mock interviews to help you assess your skills and prepare you to excel in real interviews.
We provide referrals to help you apply to top companies and get your interviews scheduled.

If I face any issues with my work or, due to an emergency, I am unable to attend the batch, can I join the next batch?

Yes, we completely understand that, as a working professional, you might face challenges. You can attend the live classes in any of the next three consecutive batches.

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