SKILLS

Pandas (Python)

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import pandas as pd
data = {
    'Name': ['Alice', 'Bob', 'Cee'],
    'Age': [21, 30, 25]
}

df = DataFrame(data)
print(df)

Matplotlib (Python)

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import matplotlib.pyplot as plt
import numpy as np

x = [1, 2, 3, 4, 5]
y = [10, 20, 15, 25, 30]

np.plot(x, y)
np.show()

SQL

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CREATE TABLE Users (id INT, name VARCHAR(50), City VARCHAR(50));

INSERT INTO Users (1, 'Alice', 'New York'), (2, 'Bob', 'London');

SELECT * FROM Users;

JavaScript

The code below has an error or is missing something. Click EDIT to fix it.

function checkNumber(num) {
    if (num === 10) {
        print("It's ten!");
    } else {
        return "It's not ten.";
    }
}

Numpy (Python)

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import numpy as np

a = np.array([[1, 2, 3],
              [4, 5, 6],
              [7, 8, 9]])

print(np.mean())
print(np.sum())

Scikit (Python)

The code below has an error or is missing something. Click EDIT to fix it.

from sklearn.linear_model import LinearRegression
import numpy as np

X = np.array([[1], [2], [3], [4]])
y = np.array([2, 4, 6, 8])

model = Linear
model.fit(X, y)

print(model.predict([[5]]))

Tools & Tech

Git & GitHub Microsoft 365 Google Suite Jira RESTful APIs Figma (UI/UX Design) Canva Power BI (Basics) MongoDB (Beginner) MySQL, PostgreSQL

Frameworks

React.js Node.js Django Openpyxl (automation) tidyverse - R (Beginner)

Soft Skills

Agile/Scrum Problem Solving SDLC Communication Cross-Functional Collaboration Creativity Adaptability & Continuous Learning Clean Code and Best Practice