Data science is widespread nowadays, with many big-name companies such as Google and Netflix looking for data scientists to reap the benefits of the data science technology to incorporate into their business analytics and analyse the user’s behaviour and interests, which they can use to improve performance related to personalized user-centric content as well as get a clear understanding of the market trends.
If you are a data science enthusiast and aspiring to be a data scientist, learning Python will definitely help you get hands-on experience in data science methods. The Knowledgehut applied Data Science with python specialization course is especially for learners who have basic to intermediate level of knowledge of Python or any other programming language and want to learn various techniques that can be applied through Python toolkits such as:
- Statistical techniques
- Machine learning
- Information visualization
- Text analysis
- Social network analysis techniques.
If this has caught your attention, read ahead to know about the course contents, eligibility, and get more information on this course.
The specialization on Python covers the basic concepts of Python and then focuses on applied data science techniques using the same programming language (ie, Python) as well as some machine learning algorithms.
The Applied Data Science with Python specialization course covers topics such as:
- Basic concepts of Python,
- Advanced concepts of Python,
- NumPy Library,
- Scipy Library,
- Pandas Library,
- Matplotlib Library,
- Seaborn Library,
- Plotlypy Library
- Introduction to Data Science,
- Case Studies in Data Science.
Let’s talk about the scope of the entire course and what you can learn from it.
The introductory part of the Python specialization component, it focuses on the fundamental concepts of Python such as mathematical functions and calculations using NumPy Library, lambda function reading files as well as CSV data manipulation using Pandas Library for importing CSV files and reading data. Here, you will be taught two important Python toolkits used for data cleaning and processing. You can also learn the basics of Pandas such as storing data into DataFrames, query data which is stored in the DataFrames, etc.
The next part of the specialization includes visualization of the data using Python libraries such as matplotlib and Seaborn to create useful visualizations using plots and charts.
The machine learning algorithms using Python come next under the specialization in which you will learn the basics of this technology as well as explicitly supervised learning techniques by making use of the Scikit-Learn library along with Classification models, Clustering, Neural Networks, etc. After you are comfortable with the fundamentals of machine learning, you will be able to learn about logistic regression and support vector machines. At this stage, you can also evaluate your ML model and infer a lot more on model selection methods.
The next thing you will learn under machine learning is text mining and text manipulation. This technology is used in AI Assistants like Siri and Alexa which can convert human language into its own machine language, process the information and then reply in the human language. In-text mining you will learn about natural language processing (NLP) using the NLTK Library along with other techniques including text classification and topic modelling for manipulating texts.
The last part of the course delves into the analysis of social networks using the NetworkX Library by learning about the different types of networks and using them to analyse the connectivity. In this part, you will also learn about how Python is integrated into the methods of data science. You will also work on some case studies that will definitely help you understand the use of data science in real-life scenarios.
Who should go for this course?
Anyone who has a basic knowledge of Python, Statistics, and Mathematics is eligible to enrol for this course. If you are a beginner, you are also eligible for this course as it begins from the fundamentals and gradually builds up your skills in Data Science. If you’re someone who is interested in learning data science using Python and is aspiring to become a Data Scientist, then this is the course that will get you started.
How long does it take to complete the course?
If you are taking the classes at a rate of 7 hours per week then you should be able to complete the course in about 5 months’ time. But then again, it should be up to you to decide the rate of your progress, as you feel comfortable. What is important is to learn throughout the course, not hang a timer above your head. So take your time and work at your own pace.
The Applied Data Science with Python specialization course is available online and provides great specialization to learn data science and become a data scientist. I hope this article has provided you with everything related to the course of Applied Data Science with Python specialization. Wish you all the best!