গুরুত্বপূর্ণ নোটিশ : আগামী ১৫ই মে, ২০২৪ রাত ১২:০০ টা থেকে সকাল ১০:০০ টা পর্যন্ত লিড একাডেমী ওয়েবসাইট মেইনটেন্যান্স এর কাজ করা হবে। উক্ত সময়ের জন্য, প্লাটফর্ম এক্সেস অস্থায়ীভাবে সীমিত থাকবে। সাময়িক অপ্রত্যাশিত অসুবিধার জন্য আমরা আন্তরিকভাবে দু:খিত। আপনার লার্নিং এক্সপেরিয়েন্সকে উন্নত করতে সহযোগিতার জন্য ধন্যবাদ।
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Learn Machine Learning with Python

Instructor
Sara Karim
Course Level
beginner
Duration
1:24:36
Rating
3.5
Students
21
Save
Share
BDT 500
Previous price1,000
  • Overview
  • Pre-requisites
  • Outcome
  • Lessons
  • Instructor
  • Reviews
  • Student Work
  • F.A.Q

About this Course

Welcome to the Machine Learning Course, brought to you by LEAD Academy!


Are you ready to explore the exciting world of artificial intelligence (AI) and machine learning? This course will introduce you to the fundamental concepts and techniques that drive modern data analysis and prediction.


Why Is This Course Important?
In today's digital age, understanding machine learning is essential for anyone interested in AI, technology and data. This course empowers learners of all backgrounds to grasp the basics of machine learning and apply them to real-world scenarios. Whether you're new to the field or looking to expand your knowledge, this course is for you.


Who Is This Course For?
This course is designed for:

  • Beginners curious about machine learning and AI
  • Tech enthusiasts eager to understand the foundations of data analysis
  • Professionals seeking to enhance their skills in predictive modelling
  • Students interested in exploring the possibilities of AI-driven technology
  • Anyone keen on understanding how data shapes our digital world

Why Should You Enroll?
By enrolling in this course, you will:
Gain a solid understanding of machine learning principles and algorithms.
Discover why Python is the preferred programming language for machine learning.


What Will You Learn?
Throughout this course, you'll:

  • Explore the basics of machine learning with practical examples.
  • Understand the importance of Python for machine learning applications.
  • Learn about essential techniques like regression, classification, and clustering.
  • Dive into real-world datasets to build predictive models and make informed decisions.
  • Gain hands-on experience with Python libraries like SLearn and how to interpret data using tools like the Confusion Matrix and Cross-Validation.
  • Explore popular regression techniques like Ridge and Lasso Regression.
  • Master classification algorithms such as Naive Bayes and Decision Trees.
  • Dive into the world of clustering with K-means Clustering.
  • Understand the power of ensemble methods like Random Forest.
  • Cikit-learn for machine learning.

Join us on this exciting journey into the realm of machine learning and AI. Enrol today and unlock the potential of data-driven insights in the digital age. Your journey to becoming a machine learning expert starts here!
 

Pre Requisites

Basic Python Knowledge

Keep video resolution at 1080p

Basic Computer Skill

What Will I Learn?

ML Basics

Python ML

Data Analysis

Model Building

Algorithm Mastery

Hands-on Skills

Python Libraries

Predictive Modeling

Topics for this course 16 Lessons

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Course Contents

Meet Your Instructor

Sara Karim
  • 3.50 Instructor Rating
  • 2 Reviews
  • 21 Students
  • 1 Course

Join Lead Academy Community

   Facebook

Language

ENGLISH , BANGLA

Learner Career Outcomes

  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Quantitative Analyst

Skills you will gain

ML Principles Data Interpretation Classification Python ML

Student Feedback

3.5

Course Ratings
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Rittique Basak
one year ago

This course is great for getting general idea for ML. I wish there were more projects or code examples from the very beginning of course to see the implementation and get more clear idea. Overall it was a decent course. I need the slides and other resoruces

Fahmida Akter
one year ago

I'm a Tech Enthusiast person for that I am pursuing ML with Python course with Instructor Sara Karim Mam. Video Quality of the Course was overall good but the timing was short. Instructor presentation and pronunciation overall okay. The main Problem is can't understand PyTorch's implementation of ML such as class 8 Implementation of K-means Clustering, class 11 IRIS Dataset Prediction and class: 10 Practical Implementation of Naive Bayes using Python. Otherwise, The course was Good for beginners who are interested in learning ML. Thank you.

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