Gain expertise in Data Science with Python and learn mathematical and scientific computing, data manipulation with Pandas, machine learning with scikit-learn, and data visualization with matplotlib.
180 Days unlimited access to Self-Paced Learning.
Alvaro is a Data Scientist who founded Quant Company and has also worked as a lead Economic analyst in the Central Bank of Guatemala. He is a M.S. in Quantitative Economics and Applied Mathematics and is actively involved in consulting and training in the data science space.
After completing this course, you will be able to:
✔ Outline what Data Science and how Python can help implement it
✔ Describe each stage of the Data Analytics process
✔ Explain basic statistical concepts relevant to Data Analytics
✔ Install the required Python environment and other auxiliary tools and libraries
✔ Review the important concepts of Python programming used to implement Data Science
✔ Demonstrate the use of the major Python libraries such as NumPy, Pandas, SciPy, scikit-learn, and Matplotlib to carry out different aspects of the Data Analytics process
✔ Employ different tools and methods to perform web scraping
✔ Illustrate Python integration with Hadoop MapReduce and Spark
The booming demand for skilled data scientists across all industries makes this course suited for individuals at all levels of experience. We recommend this data science training course especially for the following professionals:
✔ Analytics professionals who want to work with Python or Open source tools
✔ Software professionals looking for a career switch in the field of analytics
✔ Graduates looking to build a career in Analytics and Data Science
✔ Experienced professionals who would like to harness data science in their fields
✔ Anyone with a genuine interest in the field of Data Science
Prerequisites: There are no pre-requisites for this course. If you are new to analytics and Python, this is the course for you!
The Data Science with Python course explores different Python libraries and tools that help you tackle each stage of Data Analytics. Python is a general purpose multi-paradigm programming language for data science that has gained wide popularity-because of its syntax simplicity and operability on different eco-systems. This Python course can help programmers play with data by allowing them to do anything they need with data - data munging, data wrangling, website scraping, web application building, data engineering and more. Python language makes it easy for programmers to write maintainable, large scale robust code.
The course starts off with a brief introduction to Data Science, statistical concepts pertaining to Data Analytics, and a few basic concepts of Python programming. It then goes on to cover in-depth content for libraries such as NumPy, Pandas, SciPy, scikit-learn, and Matplotlib. The course also tackles important activities such as web scraping and Python integration with Hadoop MapReduce and Spark.
Submit one of the projects and on successful completion participant will receive an experience certificate
Telecommunication: Perform a service request data analysis of New York City 311 calls. You will focus on the data wrangling techniques to understand the pattern in the data and also visualize the major complaint types.
Engineering: The GroupLens Research Project is a research group in the Department of Computer Science and Engineering in the University of Minnesota. The researchers of this group are involved in many research projects related to the fields of information filtering, collaborative filtering, and recommender systems. Here, we ask you to perform the analysis through using the Exploratory Data Analysis technique. In particular, we want you to apply the tools of machine learning to predict the passengers who survived the tragedy.
✔ 40 hours of Instructor Led Training
✔ 16 assignments and 4 industry projects
✔ 24 hours of high quality eLearning
✔ 26 demos and 1 simulation exam
✔ Interactive learning with Jupyter notebooks
✔ Free Python Basics course
To get Data Scientist with Python certification, you will need to fulfil both of the following criteria:
✔ At the end of the course, you will work on a real life project. On successful completion and evaluation of the project by our expert, you will be awarded an experience certificate stating that you have worked in a real life project over a period of 3 months.
✔ At the end of the course, you will have to clear an online examination with a score of minimum 75%
Online Self-Learning:
In this mode, you will receive the lecture videos and you can go through the course as per your convenience.
At the end of the training, subject to satisfactory evaluation of the project as well as clearing the online exam (minimum 80%), you will receive a certificate from Simplilearn, stating that you are a certified data scientist with Python.
To run Python, your system needs to fulfil the following requirements:
• 32 or 64-bit Operating System
• 1GB RAM
The instruction require Anaconda and Jupyter notebooks. The e-learning videos provide detail instruction on how to install these.
The trainings are delivered by highly qualified and certified instructors with relevant industry experience.
