COURSE

Introduction

This course is designed to help you gain comprehensive knowledge and hands-on experience in Data Science, Machine Learning, and Artificial Intelligence. Through practical labs, real-world projects, and essential theory, you will develop the technical expertise to solve data-driven problems across industries like finance, healthcare, and technology.

Apply core mathematical principles—such as linear algebra, probability, and statistics—to support data science and machine learning.
Efficiently prepare, preprocess, and analyze data using Python libraries like NumPy and Pandas to build high-performance models & produce insightful visualizations.
Implement and fine-tune supervised and unsupervised learning algorithms to address a wide range of real-world challenges.
Process and extract valuable insights from textual data using modern natural language processing techniques.
Design, build, and optimize deep neural networks with tools such as TensorFlow & Keras, while exploring advanced deep learning strategies.
Data Visualization Team Collaboration

What you will learn?

Master the data science lifecycle from data acquisition to model deployment.

Student Learning

Implement exploratory data analysis and feature engineering techniques.

Student Analyzing

Apply machine learning algorithms and understand their strengths and limitations.

Student Studying

Build and evaluate NLP and deep learning models.

Student with NLP

Work with real data in a project-based environment.

Student with Data

Skillset you will acquire

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Machine learning model development

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Model evaluation and tuning

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Data wrangling and analysis

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Python programming for data science

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NLP and neural networks

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Data visualization and storytelling

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Soft Skills Overview

Communication Icon

Master communications, collaboration, and problem-solving skills required for modern tech roles.

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Practical experience in professional environments via mock interviews and real-world scenarios.

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Learn how to effectively present and collaborate in team environments.

Eligibility & Pre-requisites

To succeed in this course, students should meet the following prerequisites:

Basic understanding of mathematics, especially:

● Arithmetic operations   ● Algebra and basic equations   ● High-school level probability and statistics

Introductory awareness of AI/Data Science concepts (recommended but not mandatory)

Basic knowledge of any programming language (Python is preferred but not mandatory)

Course outline