Course Overview

Our Data Analytics course is designed to provide you with essential skills and knowledge to excel in data science. The program lasts four months, with 2.5 months dedicated to intensive coursework and a 1.5-month internship.

  • You will participate in two weekly online lessons, each lasting 1.5 hours.
  • These lessons are provided by experienced professionals who will share practical insights and high-quality instruction.
  • The course covers a wide range of topics to prepare you for real-world challenges in data analytics.
  • After completing the coursework, you will start a 1.5-month internship to gain hands-on experience and apply your new skills professionally.

Join us to develop a strong foundation in data science and gain the practical experience needed to move forward in this dynamic field.

Course curriculum

  • 1

    Getting Started with Python

    • Course Overview & Setting Up Python Environment

    • Python Basics (focusing on data structures and functions)
  • 2

    Foundations of Pandas

    • Introduction to Pandas & Series/DataFrame Basics

    • Pandas: The Data Wrangler

    • Data Filtering & Boolean Masking

    • Grouping & Aggregation
  • 3

    Intermediate Pandas Operations

    • Merging & Joining DataFrames

    • Essential Reshaping & Advanced Functions

    • Working with Time Series Data

    • Creating Summary Reports & Business Metrics
  • 4

    Data Quality & Preparation

    • Handling Missing Data

    • Working with Different Data Types & Text Data

    • Using Excel with Python (pandas integration with Excel)

    • Building Automated Data Quality Reports
  • 5

    Data Visualization & EDA

    • Basic Plotting with matplotlib

    • Creating Professional Visualizations with seaborn

    • Interactive Visualizations (plotly basics)

    • Exploratory Data Analysis Techniques
  • 6

    Introduction to Machine Learning

    • ML Fundamentals & Simple Classification

    • Basic Regression Analysis
  • 7

    Final Project

    • Project Work Session 1

    • Project Presentations & Course Wrap-up
  • 8

    Internship

    • Internship