Course Overview:

The Applied Data Science course is designed to equip students with the essential skills and knowledge required to excel in the field of data science. The course consists of five comprehensive modules that cover key areas of data science, including Python programming, data science fundamentals, machine learning, SQL, and Intro to Deep Learning. Throughout the course, students will gain hands-on experience by working on real-world projects, applying their knowledge to solve complex data problems, and developing practical solutions using various data science tools and techniques.

Module 1: Python Programming

In this module, students will delve into the fundamentals of Python programming language, including object-oriented programming (OOP) concepts and regular expressions, and their application in data science.

Module 2: Data Science Fundamentals

This module focuses on the core concepts and techniques in data science. Students will learn about data preprocessing, exploratory data analysis, feature engineering, and data visualization. They will also gain an understanding of statistical concepts and learn how to apply them in data science projects. By the end of this module, students will be equipped with the necessary skills to extract insights from data and communicate their findings effectively.

Module 3: Machine Learning

 In this module, students will dive into the exciting world of machine learning. They will learn various supervised and unsupervised machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, and clustering techniques. Students will gain hands-on experience by building and evaluating machine learning models on real datasets. By the end of this module, students will have a solid understanding of machine learning algorithms and their application in solving real-world problems.

Module 4: SQL

This module focuses on Structured Query Language (SQL) and its role in data manipulation and analysis. Students will learn how to retrieve and manipulate data from relational databases using SQL queries. They will gain practical skills in database management, data extraction, and data manipulation. By the end of this module, students will be proficient in SQL and will be able to leverage its power to analyze and extract valuable insights from large datasets.

Module 5: Introduction to Deep Learning

In this module, we’ll explore powerful neural networks capable of solving complex problems. In this module, students will dive deep into the world of deep learning, learning about neural network architectures and their applications in solving real-world challenges.

Upon completion of the Data Science course, students will have the skills to apply for various roles in the data science field, including:

1. Data Analyst: Utilize your skills in data analysis and SQL to uncover patterns, trends, and insights, while creating compelling data visualizations using tools like Power BI.
2. Machine Learning Engineer: Design and implement machine learning models, optimize algorithms, and deploy them in production environments, leveraging your expertise in machine learning algorithms.
3. Python Developer: Utilize your strong foundation in Python programming to design, develop, and maintain Python-based applications, contributing to the development of data-driven solutions in various industries.
4. Data Engineer: Design and maintain data infrastructure, constructing and optimizing data pipelines, integrating data, and working with big data technologies to ensure data availability, integrity, and efficiency.

By completing the Applied Data Science course, you will be well-prepared to pursue these exciting roles and make valuable contributions in the dynamic field of data science.

Recommended Professional Certificates:

·       IBM Data Analyst Professional Certificate

·       Google Data Analytics Professional Certificate