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A lot has happened in the year 2023 and some of you are probably considering transitioning into a data science career. You may be wondering where to start. What course should I take? Do I need to know something beforehand?
This is where KDnuggets is here to help answer all those questions!
The KDnuggets team have created a data science pathway for all of our readers to benefit, regardless of their walk of life.
Want to know more?
Link: Python Programming & Data Science Foundations
In the first week, we will be learning all about Python, Data Manipulation, and Visualisation.
Day 1 to 3: Python Essentials for Aspiring Data Scientists
- An introduction to Python’s role in data science.
- A beginner-friendly guide to Python’s syntax, data types, and control structures.
- Interactive coding exercises to solidify your understanding.
Day 4: Python Data Structures Demystified
- Learn about Python’s core data structures with our step-by-step guide. You’ll learn about lists, tuples, dictionaries, and sets each with practical examples and their significance in data processing.
Day 5 to 6: Practical Numerical Computation with NumPy and Pandas
- Discover the power of NumPy and Pandas for numerical analysis and data manipulation, including real-world applications and hands-on exercises.
Day 7: Data Cleaning Techniques with Pandas
- Equip yourself with essential data-cleaning skills using Pandas.
Link: Database, SQL, Data Management and Statistical Concepts
Moving onto the second week, we will learn about Database, SQL, Data Management and Statistical Concepts.
- Day 1: Introduction to Databases in Data Science
- Day 2: Getting Started with SQL in 5 Steps
- Day 3: Data Management Principles for Data Science
- Day 4: Working with Big Data: Tools and Techniques
- Day 5: Statistics in Data Science: Theory and Overview
- Day 6: Applying Descriptive and Inferential Statistics in Python
- Day 7: Hypothesis Testing and A/B Testing
Link: Introduction to Machine Learning
Moving onto the third week, we will dive into machine learning.
- Day 1: Demystifying Machine Learning
- Day 2: Getting Started with Scikit-learn in 5 Steps
- Day 3: Understanding Supervised Learning: Theory and Overview
- Day 4: Hands-On with Supervised Learning: Linear Regression
- Day 5: Unveiling Unsupervised Learning
- Day 6: Hands-On with Unsupervised Learning: K-Means Clustering
- Day 7: Machine Learning Evaluation Metrics: Theory and Overview
Link: Advanced Topics and Deployment
Moving onto the third week, we will dive into advanced topics and deployment.
- Day 1: Exploring Neural Networks
- Day 2: Introduction to Deep Learning Libraries: PyTorch and Lightening AI
- Day 3: Getting Started with PyTorch in 5 Steps
- Day 4: Building a Convolutional Neural Network with PyTorch
- Day 5: Introduction to Natural Language Processing
- Day 6: Deploying Your First Machine Learning Model
- Day 7: Introduction to Cloud Computing for Data Science
Link: Deploying to the Cloud
Moving onto the bonus week:
- Bonus 1: Getting Started with Google Platform in 5 Steps
- Bonus 2: Deploying your Machine Learning Model to Production in the AWS Cloud
And just like that, you have gone through a 5-week pathway to kickstart your data science career! The team at KDnuggets hope we have equipped you with the knowledge and tools that you need to progress your data science career!
Let us know what you enjoyed in the comments!
Nisha Arya is a Data Scientist and Freelance Technical Writer. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.
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- Source: https://www.kdnuggets.com/back-to-basics-pathway?utm_source=rss&utm_medium=rss&utm_campaign=back-to-basics-pathway
