DATA ANALYSIS AND WRANGLING WITH PYTHON
40Hrs Part-Time | 6 Weeks
Learn the right techniques to wrangle the collected Data
GRANTS AVAILABLE FOR SG/PR*
About Advanced Data Science Course
Data wrangling is the time and effort data scientists and software developers put in to prepare data for the meaningful insights you want to acquire from data exploration and data analytics. Data Analysis and Data Wrangling is a 40-hour advanced Python course that helps the student to master the foundations of acquiring and loading raw data from diverse sources and manipulating it efficiently to fulfil corporate objectives in this course.
The course will cover basic programming abilities in Python, such as variable types, operations, user input/output, logic, loops, functions, and object-oriented programming, over the course of six weeks will cover Advanced Python Principles, Project File Management, and Rudimentary Error Handling and Testing. Through hands-on activities, you can use Python to apply suggested programming practices such as documentation and naming conventions to produce coding solutions. Students will also learn industry best practices for handling various sorts of data, as well as acceptable data manipulation and coding procedures, as well as work on real-world business challenges with non-trial datasets. This course will provide the learner with the required skills and resources to successfully complete the course.
SHORT COURSE OVERVIEW
Learn advanced data management skills for Python, guided by Industry Experts!
Embark on a 6-week journey with us, where you’ll learn to collect, organize, and interpret data, using advance Python Programming techniques.
Guided by industry experts, you will tackle real-world data challenges, learning to source data from various platforms and transform it into a powerful tool for decision-making.
Join us now and pave your path to becoming a Data Analyst, ready to drive the future of data-driven innovation!
DURATION: 40Hrs (Mondays and Wednesdays, 7:30PM – 10:30PM SGT)
COURSE CODE: TGS-2022011217 (CLASSROOM & ASYNCHRONOUS E-LEARNING)
GRANTS AVAILABLE: SSG, SFC, PSEA
AWARD OF CERTIFICATE: Statement of Attainment
Software Taught: Python
Note: Customisation Available for Corporate Clients
INSTRUCTORS
TOPICS COVERED
- Understanding the Business Domain and its requirements
- Import Data Sets
- Types of Data using tools and techniques
- Understanding the Dataset – Quality and Quantity
- Tools and Techniques for Data Analysis
- Importing and Exporting Data in Python
- Chosen Data sets
- Clean and prepare Data for analysis
- Manipulate Data Frame
- Summarize Data
- Insights from Data
LEARNING OUTCOMES
- Select the best tools and learn the right techniques to wrangle the collected Data
- Evaluate and analyse the Data using appropriate tools and techniques based on business objectives to maximize
- Derive insights by performing visual analysis on real world Data and articulate how these insights impact business decisions and lead to improved business objectives
ADDITIONAL INFORMATION
UPCOMING INTAKES
TBD
ENTRY REQUIREMENTS
- Age: 18 years and above
- Education : N Level and Above
- Language : English (Spoken & Written)
- Prerequisite : Basic Knowledge of Computers and Using Productivity Software
Entry Requirements
- Passion for Programming.
- Intend to seek a career switch in the Data Analytics Vertical
- Minimum Education Level – N Level
- Work Experience (No. of Years) – N.A
- Age – 18 years and Above
- Language (Written) – English Language (Spoken) – English
- Language (Written) – English
- Workplace Literacy and Numeracy Level (WPLN) >= 6
- Computer Skills – Basic
Basic Knowledge of Computers
- Start up, log on, and shut down a computer system properly.
- Use a mouse-pointing device and keyboard.
- Identify and use icons (folders, files, applications, and shortcuts/aliases)
- Minimize, maximize, and move windows.
- Check how much space is left on a drive or other storage device.
Proficiency in Using Productivity Software
Understand and know how to use the following types of software programs:
- Word processing (example: MS Word, Google Doc, Writer)
- Presentation (example: PowerPoint, Impress)
- Compression software (example: WinZip, Stuff It, 7-Zip)
Moving Files
- Transfer files by uploading or downloading.
- View and change folder/document security settings.
Copy files from hard disk to storage devices and vice versa
COURSE FEES
(*All fees include 8% GST)
Full Course Fees: SGD 2,808
PR/Singaporean 21 – 39 Yrs/Non-SME Company Sponsored Singaporean & PR: SGD 1,508
Singaporean above 40Yrs/SME Company Sponsored Singaporeans & PR: SGD 988
Registered Course Name (MySkillsFuture Website) : DATA ANALYSIS AND DATA WRANGLING WITH PYTHON (Classroom & Asynchronous e-Learning)
Registered Course Code/ID : TGS-2022011217
- Self-sponsored students can use SSG Training Grant, Skills Future Credit, PSEA grant, UTAP, and SEP.
- 75% attendance is mandatory to complete the program
- The student should submit and must pass the prescribed assessment (i.e. Practical Project)
- *For additional grant eligibility, please contact us.
FREQUENTLY ASKED QUESTIONS
Who is this program for?
- Age: 18 years and above Education : N Level and Above
- Language : English (Spoken & Written)
- Prerequisite : Basic Knowledge of Computers and Using Productivity Software
Do I need to know coding for these courses?
No, it’s not mandatory for you to know coding for this program.
What is this course all about?
In this course, learners understand the foundational knowledge of Data Science and identify its benefits for real-world applications. Concepts from the contributing field of interaction design will be also introduced in the context of augmented reality.
By the end of the course, the learner would have developed a working prototype of an Immersive Data Science application based on a concept.
What is the admission process and payment options are available?
Once we receive your contact information the course consultant will contact you he/she will guide you through the admissions process and the grants that are available for you.
We accept payments by check, bank transfer, credit/debit card and PayPal. For more information, please contact us directly using the form below.
SPEAK TO AN ADVISOR
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