Study Plan
Learn Data Analytics from scratch. Students will understand the logic of the Python programming language, use UNIX terminals and the most popular tools for data visualization. By the end of the program, they will have acquired the most widelyused skills and techniques in the world of data analytics.
1. Prework
The Prework phase introduces concepts that the course will analyze in greater depth, ensuring students feel grounded from day one and bringing the entire group to a common level. This not only ensures that the group can move forward together, but also helps create a collaborative environment among all members.
- Computer basics: Concepts including hardware and software, CPU, memory, storage devices, operating systems and networks.
- Introduction to programming languages: Explanation of what a programming language is, what it is used for, and the types of languages that exist (compiled and interpreted). An overview of the most commonly used languages today, and why they are used.
- Fundamental programming concepts: Discussion of variables, data types, operations, control flow structures (if/else, loops), and functions. How to break down a complex problem into smaller, more manageable subproblems. Issues are explained in a basic way to avoid overlapping with the Programming Fundamentals module (with Python).
- Development tools and best practices: Introduction to the use of an IDE, such as PyCharm or VSCode, as well as notebooks. Discussion about version control with Git. Underlining programming best practices, such as the importance of commenting code and following style conventions (Pythonic Code).
- Introduction to data structures: Overview of concepts such as arrays, lists, sets, dictionaries/maps and trees. The focus is not confined to a specific programming language, but also at pseudocode level. The aim is for students to understand what they are, what they are used for, and when it might be appropriate to use one data structure over another.
- Fundamental database concepts: Explanation of what a database is, what it is used for, and the various types that exist (e.g. relational and non-relational databases).
2. Fundamental Concepts of Programming
Students learn to program in Python, a popular and powerful programming language used in many contexts, such as creating web applications, analyzing data, creating artificial intelligence programs, and even controlling robots. It is an easy language to learn and has clear and simple syntax, making it is easy to read and write. Students learn the various fundamental concepts of Python, including control structures, lists, dictionaries or functions, so by the end of the module they will have the basic knowledge required to get through the rest of the bootcamp.
- Introduction and basic features
- Data types, variables and text manipulation
- Tuples, lists, dictionaries and sets
- Random
- Flow control structure
- Functions
- Dates
- Lambda
- Regular expressions
- Json
3. Artificial Intelligence (AI) Fundamental Concepts
- Introduction to AI
- Towards ML
- Artificial neural networks
4. Data Manipulation and Processing
- Introduction to data science
- Data analysis and processing
- Digital surgery
- Data visualization
5. Data Visualization
- Introduction to visualization
- Tableau
- Google Data Studio
- Microsoft Power BI
- Other tools
6. Machine Learning
- Supervised systems
- Non-supervised systems
- Neural networks
7. Capstone Project
- Definition of the idea with an assigned tutor
- Selecting the project aim
- Deciding methodologies and tools
- Presentation before a jury of experts and colleagues