Learn Data Manipulation and Cleaning, Exploratory Data Analysis, Statistical Analysis, Basics of ML ML in Python
Sub Category
- Data Science
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Objectives
- You will understand the Introduction to Data Science and Python, starting with the definition, importance, and applications of data science in real-world
- You will explore Data Manipulation and Cleaning, covering data import and export from formats like CSV, Excel, and JSON
- You will gain expertise in Exploratory Data Analysis (EDA) using visualization tools such as Matplotlib and Seaborn to create bar, line, and scatter plots
- You will work with Statistical Analysis in Python, focusing on hypothesis testing with both parametric and non-parametric tests
- You will master the Basics of Machine Learning, understanding supervised vs. unsupervised learning, evaluation metrics
- You will explore Machine Learning Algorithms in Python, covering supervised learning algorithms like decision trees, random forests, support vector machines
- You will advance into Advanced Topics in Data Science covering, Feature Engineering, Deep Learning, and Model Interpretability
- You will dive into Deep Learning with Python, building models using TensorFlow and Keras, including convolutional neural networks
- You will gain hands-on experience in Big Data Analytics with Python, learning Apache Spark, PySpark, distributed data analysis
- You will apply your skills through Applied Data Science Projects, learning how to design, implement, and present data science solutions
Pre Requisites
- You should have an interest in data science, programming, and how data can be used to extract insights and build intelligent systems.
- A desire to learn how to collect, clean, manipulate, and analyze data using Python and essential libraries like Pandas, NumPy, Matplotlib, and Seaborn
- Interest in real-world data science use cases, including exploratory data analysis, machine learning, deep learning, and big data analytics.
- Basic familiarity with Python programming (variables, loops, functions) and an understanding of basic math/statistics is recommended.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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