1. Finance (Quant, Risk, Data Analytics) ✅ Key Skills to Develop: Financial modeling, time series analysis Probability, statistics, and stochastic processes Machine learning applications in finance Python (pandas, NumPy, scikit-learn), R, SQL Tools: Bloomberg Terminal, Excel (VBA), Power BI ✅ What to Do: Take a Financial Engineering/Quantitative Finance course Learn algorithmic trading and practice on platforms like QuantConnect or Kaggle Earn certifications like CFA (Chartered Financial Analyst) or FRM (Financial Risk Manager) Apply for Quantitative Analyst, Risk Analyst, or Financial Data Scientist roles 🔗 Where to Apply: Investment banks, hedge funds, asset management firms, fintech startups Example Role: Quantitative Analyst at Goldman Sachs - Develop statistical models for risk assessment - Implement trading algorithms in Python and R - Analyze financial trends and optimize investment strategies 2. Tech (Data Science, AI, Software Development) ✅ Key Ski...
Exercise 1: Create a program that asks the user to enter their name and their age. Print out a message addressed to them that tells them the year they will turn 100 years old. Note: For this exercise, the expectation is that you explicitly write out the year (and therefore it will be out of date the next year). Solution 1: name = input("Please, enter your name here: ") age = input("Please, enter your age here: ") age = int(age) current_year = input("Please, enter the current year here: ") current_year = int(current_year) year_turning_100 = current_year - age + 100 print(name, "you will be 100 years old in", year_turning_100) Example Output: Please, enter your name here: Mofasa Please, enter your age here: 34 Please, enter the current year here: 2025 Mofasa you will be 100 years old in 2091 By Youssaf Menacer, PhD