Enroll Course: https://www.udemy.com/course/pythondatascientist/
Are you looking to break into the exciting field of Data Science or enhance your existing skills? The “เรียน Python เพิ่มทักษะการทำงานสายอาชีพ Data Scientist” course on Udemy is a fantastic option designed to take you from a foundational understanding of Python to becoming proficient in data analysis, machine learning, and visualization.
This course is structured to be a “Zero to Hero” journey, but it’s important to note that a prerequisite of prior Python programming knowledge is recommended to get the most out of it. If you’re new to Python, it might be beneficial to complete a basic Python course first.
The curriculum is meticulously divided into five comprehensive sections:
**Part 1: Python Programming Tutorials**
This foundational section covers the essentials of Python programming, including syntax, variables, operators, conditional statements, loops, and data structures like lists, tuples, sets, and dictionaries. It’s packed with exercises to solidify your understanding.
**Part 2: Python for Data Science Tutorials**
Here, you’ll dive into the core concepts of data science using Python. This includes reading and writing files, working with CSV files, and introductions to powerful libraries like NumPy and Pandas. Data cleaning and basic data analysis and visualization techniques are also introduced.
**Part 3: Python Data Cleaning**
Data cleaning is a crucial step in any data science workflow. This section offers in-depth tutorials and practical exercises focused on various data cleaning techniques, ensuring you can prepare your datasets effectively.
**Part 4: Python for Machine Learning**
This is where the course truly shines for aspiring data scientists. You’ll explore the mathematical and statistical underpinnings of machine learning, followed by practical applications of supervised learning (Linear Regression, Decision Trees) and unsupervised learning (Clustering). The course bridges the gap between these concepts with a practical decision tree and clustering overview.
**Part 5: Python for Data Visualization**
Communicating insights is key. This extensive section covers a wide array of data visualization techniques using Python. You’ll learn to create various chart types, including line charts, bar charts (vertical, horizontal, stacked), scatter plots, pie charts, histograms, and combo charts, all with hands-on exercises.
**Overall Recommendation:**
This course is highly recommended for anyone serious about pursuing a career in Data Science. The structured approach, extensive coverage of essential Python libraries, and practical exercises make it an invaluable resource. While the prerequisite is noted, the depth of content in each section ensures that learners will gain robust skills. The hands-on nature of the exercises is particularly commendable, as it allows for practical application of learned concepts.
If you’re ready to invest in your data science journey and build a strong foundation in Python for this field, this Udemy course is an excellent choice.
Enroll Course: https://www.udemy.com/course/pythondatascientist/