One-shot finish! Big Data Analysis Engineer Practical Work Type

A chance for those who don't know how to nose it 🙌
Challenge the Big Quarter practical skills with just one lecture!

Introduction to Coding + Machine Learning
Let's finish it in one go!

The Big Data Analyst Certification Exam, which debuted in late 2020, has been garnering significant attention!
However, for those who are new to coding and machine learning, it may sound like a distant dream.

This course is an introductory course on data/machine learning designed for those people.
Our goal is to provide guidelines for even the most novice Python learners to pass the Big Data Analyst practical exam with minimal knowledge. During the approximately 10-hour lecture period, we focus on the essentials, ensuring you pass the exam without missing anything.

The curriculum is designed to allow for repeated learning simply by listening to the lectures .
Master the content perfectly and pass the exam with minimal time and effort!

If you know just this much
Enough ✅

Attention, these people!

Machine Learning &
Python coding
First time encountering

Big Data Analysis Engineer
Practical test
Applicant

Even if you have to memorize it
The will and desire to pass
Anyone who has

Time and cost
I want to cherish
Lightning strike group

I passed the Big Data Analyst practical exam last year without any textbooks or practice questions. This course was carefully designed based on my own experience preparing for the exam, taking into account various issues and environmental constraints. I received feedback from my girlfriend, who had no prior coding knowledge, to develop the course, and I plan to further refine it through Q&A sessions with you.

This course covers the essential core concepts concisely enough to make you wonder , "Is this really enough?" I'll help you prepare for the exam and pass it just by memorizing it mechanically. 😊

Key Learning Point!

• 1️⃣ Learn how to use the programming language, Python.
• 2️⃣ Experience Google Colab, which is widely used for actual ML/DL learning.

Only in this lecture
Two key advantages ✨

What is covered in the lecture
Check it out 📚

👉 If you are considering a career change in a related field,
We help you achieve realistic 'take-and-eat' !

Section 0. Orientation

We will explain how to use Colab and the future direction of the lecture.

Section 1. Python Basics

Learn the basics of Python usage, data types, etc.

Section 2. Python Grammar

Learn about Python's basic grammar, including conditional statements, loops, and exception handling.

Section 3. Pandas Basics

Learn the basics of Pandas, a library for handling data.

Section 4. Pandas Basics

Learn how to manipulate data with Pandas.

Section 5. Pandas Intermediate

Learn how to solve more challenging problems using Pandas (some of the tasks in Task 1 fall into this category).

Section 6. Machine Learning Basics

Learn about the overall structure and techniques of machine learning.

Section 7. Machine Learning Basics

We solve problems with a high probability of appearing on the exam using machine learning.

Section 8. Perfect preparation for the real thing!

As our student body grows, we will continue to add more practice exam questions!

Created this course
Knowledge sharer is 👨‍🏫

Check out the Q&A !