The full course fees for this training is S$980, before any Government funding.
For Singaporean/PR above 21 years, Training Grants are available.
For Foreigners, no government grants are available.
WSQ funding from SkillsFuture Singapore (SSG) is available to Singaporeans/PRs above 21.
(Both Individuals & Company Sponsored ).
Individual Singaporeans, 25 years & above can also use their SkillsFuture Credits for this training at Intellisoft.
NTUC Members can utilize UTAP Funds to offset 50% of the remaining fees*.
Contact us for more information on How to apply for this SkillsFuture Grant.
Call +65-6252-5033 for Details or WhatsApp Now at +65-9066-9991
The Analyze and Visualize Data With Python Training is a practical, hands-on, 2 days training, focused on teaching the participants the key skills used to analyze data using Python.
This intermediate 2-day course focuses on a number of Python packages that are commonly used for data analysis, including: CSV, Numpy, SciPy and Pandas. During the course, participants will manipulate and clean data as well as use the stats library to conduct basic statistical tests.
Additionally, this course focuses on how to write and run simple data analysis programs in Python, and builds on these using some of the powerful extensions available in Python. This will be achieved through hands-on worked examples of real life data problems.
Python is used by analysts who want to go deeper into data analysis or apply statistical techniques, and by most people who turn to Data Science, Machine Learning, Artificial Intelligence, Big Data analysis.
Python is a production-ready language meant for data science and data analysis, meaning it has the capacity to be a single tool that integrates with every part of your workflow! It helps you make sense of your data, quickly, and efficiently.
On this course, you’ll also look at:
For this course, you’ll need some basic experience with Python. You can do our Beginners in Python course first if you do not have the basics yet.
Pandas allows us to analyze big data and make conclusions based on statistical theories.
Pandas can clean messy data sets, and make them readable and relevant.
Relevant data is very important in data science.
Pandas gives you answers about the data. Like:
Pandas are also able to delete rows that are not relevant, or contains wrong values, like empty or NULL values. This is called cleaning the data.
Data Analysis With Pandas
Data Analysis Project With Pandas & Python.
This course is for people who want to analyze a lot of data quickly and gain insights that are not available easily.
We use the Python programming language, which is popular among data analysts and data scientist.
A number of popular Python libraries and packages like Numpy, Pandas and SciPy are covered in this training. If you wish to learn how to use Python for Data Analysis, then this training is for you.
This Python course is designed for intermediate users who wish to become an application developer by using Python, which is a widely used general-purpose, high-level programming language. It is a classroom-based course that covers the essential topics to start programming with Python.
Basic prior knowledge on Python programming is required. If you don’t have the basics of Python, we recommend that you attend the Introduction to Python training first.
WSQ: To claim up to 70% WSQ Funding for this Analyze and Visualize Data With Python training, participants must be Singaporeans or PRs. They can be INDIVIDUALS or COMPANY SPONSORED. We will apply for the WSQ Grant on your behalf, AFTER you have successfully registered for this training. SSG Terms and conditions apply for WSQ Funding, based on your/your company’s eligibility.
SkillsFuture for Analyze and Visualize Data With Python Training: Individual Singaporeans aged 25 and above can use their SkillsFuture Credits for this Basic Excel training class.
UTAP Funding: NTUC Members can utilize UTAP to offset 50% of the remaining fees*.
Call us at +65 6250-3575 or email training@intellisoft.com.sg for any questions or to register for the upcoming class of Analyze and Visualize Data With Python course with SkillsFuture & WSQ funding.
Note: This class is a very practical, and hands-on workshop session. It requires you to take part in a lot of exercises during the class. A laptop with the required software pre–loaded is provided to each participant for use during this workshop.
Join Python class in Singapore today, and learn the Fundamentals of Python Data Analysis easily, with step by step instructions, and helpful, patient, Certified Trainers to guide you.
We also provide Corporate Training on Analyze and Visualize Data With Python in Singapore, and Asia, provided you have a group of participants wanting to learn Python Data Analysis.
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We are located at Fortune Centre, 190 Middle Road, #10-08 Singapore 188979
Telephone: 6252-5033 WhatsApp: 9066-9991
Email: info@trainingint.com
In a Python for data analysis training, you can expect to learn various libraries and techniques commonly used for working with data. Here are some key topics that are typically covered:
Introduction to Python for Data Analysis: The training will start with an introduction to Python programming language and its relevance in data analysis. You will learn about basic data types, variables, control flow, and functions in Python.
Pandas: Pandas is a powerful library for data manipulation and analysis. You will learn how to work with Series and DataFrame objects, load data from different sources (such as CSV, Excel, and databases), clean and preprocess data, handle missing values, and perform various operations like filtering, grouping, merging, and reshaping data using Pandas.
Data Visualization: Visualization is an essential aspect of data analysis. You will learn how to create meaningful visualizations using libraries such as Matplotlib. Topics covered may include plotting data, customizing plots, creating bar charts, line plots, scatter plots, histograms and more.
Exploratory Data Analysis (EDA): EDA involves analyzing and summarizing datasets to gain insights and identify patterns. You will learn how to explore and visualize data using Pandas and other libraries, handle outliers and anomalies, perform descriptive statistics, and generate summary statistics.
Statistical Analysis: The training may cover statistical techniques commonly used in data analysis. This may include hypothesis testing, confidence intervals, correlation analysis, and regression analysis. You might also learn about probability distributions and statistical modeling.
Data Wrangling and Cleaning: Data analysis often involves dealing with messy and incomplete data. You will learn various techniques for data wrangling and cleaning, such as handling missing data, handling duplicates, transforming data, and dealing with outliers.
These are some of the core topics you can expect to learn in a Python for data analysis training.