Course

Data Science

This course equips you with the essential skills to become a successful Data Scientist. Learn data analysis, machine learning, visualization, and predictive modeling using real-world datasets and industry tools to build data-driven solutions.

Course Overview

In this course, you will learn the entire process of building powerful web applications with Python, Django, React and modern web development techniques step-by-step. You will learn to build beautiful UI’s and secure backend systems as well as manage databases, build APIs and deploy applications onto live servers. More importantly, you will be working on real projects that will help you understand how development in actual companies and software teams actually happens. By the end of the course you will not only know coding concepts, you will know how to build complete full stack applications by yourself.

Modules

1. Introduction to Data Science

Basics of extracting insights and knowledge from data.

2. Python Programming for Data Science

Using Python programming for data analysis and automation.

3. Advanced Python & Libraries

Learning advanced Python concepts and popular data science libraries.

4. Statistics & Mathematics for Data Science

Understanding mathematical and statistical foundations for analysis.

5. Data Collection & Data Cleaning

Gathering, organizing, and preparing data for analysis.

6. NumPy & Pandas

Using Python libraries for numerical computing and data manipulation.

7. Data Visualization with Matplotlib & Seaborn

Creating charts and graphs to visualize data insights.

8. SQL for Data Analysis

Querying and managing databases for data analysis tasks..

9. Exploratory Data Analysis (EDA)

Analyzing datasets to discover patterns and trends.

10. Machine Learning Fundamentals

Introduction to algorithms that learn from data.

11. Supervised & Unsupervised Learning

Building models for prediction and pattern discovery.

12. Model Evaluation & Optimization

Improving model accuracy and performance using evaluation techniques.

13. Deep Learning Basics

Learning neural networks and AI-based data processing methods.

14. Natural Language Processing (NLP)

Enabling computers to understand and process human language.

15. Power BI & Data Visualization Dashboards

Creating interactive dashboards and business reports using Power BI.

16. Real-Time Projects & Capstone Project

Applying learned skills to practical industry-level projects.

Features

Practical Training

Each concept is taught through hands-on practice, real datasets, and industry-based case studies.

Real-Time Project

Gain practical experience by working on live Data Science and Machine Learning projects.

Expert Mentors

Learn directly from experienced Data Scientists, industry professionals, and trainers.

Interview Preparation

Special training for technical interviews, aptitude, resume building, portfolio creation, and career guidance.

Flexible Learning

flexible learning options available for both online and offline students.

Placement Assistance

Guidance and support for internships, project opportunities, and Data Science job placements

What Makes Appzia Learnx Different?

Industry-Focused Learning

Our curriculum is designed according to the current industry needs and technologies.

Learn by Building

We think that students learn better when they are building real applications, not just learning theory.

Personal Guidance

We mentor and support you throughout your learning journey.

Portfolio Development

Students work on projects that directly contribute to their professional portfolio.

Career Support

We prepare students for actual opportunities in the IT industry, from interview preparation to placement guidance.

Friendly Learning Environment

We want to create a positive and encouraging learning experience for all students.

Course Duration

Total Length: 1 hour 35 minutes

Explore opportunities