Udemy – Data Science: Your Path to AI & Insights into Data

Tired of not knowing where to start with your data, wasting time cleaning CSV files, or not understanding why your model isn’t working? This course will guide you step by step — from your first lines of code to your own predictive models.

Whether you’re a Python beginner or already have a programming foundation, this course will transform you into a Data Science practitioner. You’ll learn to manipulate, analyze, visualize, and model data like a professional.

No more messy scripts, incomprehensible errors, and hours lost on Google. It’s time for clear, structured, and efficient Data Science practice.

Course Structure – What to Expect

• Introduction to Data Science What is data science, why is it essential today, and what are the key skills to master?
• Statistical Fundamentals for Data Science Learn essential concepts: mean, standard deviation, distributions, correlation vs causality, p-values, A/B testing…
• Python for Data Science Master Python data structures (lists, dictionaries, sets, etc.) and learn modern techniques like comprehensions.
• Data Manipulation with Pandas Importing, cleaning, filtering, grouping, merging… You’ll know everything about data preparation.
• Numerical Calculations with NumPy Create and manipulate high-performance numerical arrays, and perform vectorized calculations.
• Data Visualization Learn to create impactful graphs with Matplotlib and Seaborn: histograms, scatter plots, heatmaps, boxplots, and more.
• Machine Learning with Scikit-Learn Build supervised and unsupervised models, test them, optimize them, and understand their performance.
• Deep Learning with TensorFlow & Keras Create your first neural networks, CNNs, RNNs, and even explore GANs to generate your own data.
• Final Project: Complete Application A concrete project where you’ll implement everything you’ve learned: cleaning, visualization, modeling, and prediction.

• Python Developers: Developers seeking to expand their skills into the field of data science, analysis, and machine learning.
• Students and Researchers: Those who need to understand and apply data science methods for their academic or research projects.
• Professionals in Career Transition: Anyone wishing to embark on a career in data science and master the essential tools of the industry.
• AI and ML Enthusiasts: Anyone eager to understand machine learning and deep learning algorithms and their practical applications.
• Future Data Scientists: Those aiming for a Data Scientist career and wanting to master the technical skills demanded by companies.
• Developers wishing to optimize their solutions with predictive models and AI.