- Learn how to utilise python for data analysis.
- Use python as a platform for data ingestion and manipulation.
- Exploratory data analysis methods.
- Data model building and visualisation.
- Learn how to use data to support your own hypothesis.
DATA ANALYTICS USING PYTHON
Duration: 16 Hours
Required Skills:
Basic understanding of Python
IT Savvy
Course Fee: $1,070
This course is eligible for:
Participants will be taught the usage of the key libraries for data ingestion and manipulation, exploratory data analysis, model building and data visualization as well as basic statistic knowledge required to understand concepts in the latter portion of the course.
Programme Objectives:
Learning Outcomes:
Programme Objectives:
- Understand what is Data Analytics.
- Learn Data Manipulation.
- Import Data using Python and basics of analyzing data.
- Understand how to clean data.
- Learn about descriptive statistics and the importance of visuals.
- Visualize and analyze data.
- Create various interactive charts and learn how to format those charts..
Learning Outcomes:
- MODULE 1: Understanding Data.
- MODULE 2: Data Wrangling.
- MODULE 3: Exploratory Data Analysis.
- MODULE 4: MODULE 4: Data Visualization.
- MODULE 5: Hypothesis Testing.
Participants are eligible for IBF enhanced course fee subsidies up to 90%.
Eligible Individuals Include:
Programme(s) Commencing between 1 Jan 2022 till 30 Jun 2022
- Company-sponsored individuals or self-sponsored participants
- Singapore Citizens or Singapore Permanent Residents, physically based in Singapore
- Successfully completed IBF-STS recognized programme (Achieve min. 75% attendance and pass all assessment components)
Programme(s) Commencing between 1 Jan 2022 till 30 Jun 2022
For Singaporeans
below the age of 40 & Singapore Permanent Residents of all age groups
below the age of 40 & Singapore Permanent Residents of all age groups
| Data Analytics using Python Course Fee |
$1,000 |
| Add 7% GST |
$70 |
| Deduct Enhanced Funding Support (80%) – Inclusive of GST |
$856 |
| Total fee payable by self-funded individual |
$214 |
For Singaporeans
Aged 40 and above
| Data Analytics using Python Course Fee |
$1,000 |
| Add 7% GST |
$70 |
| Deduct Enhanced Funding Support (90%) – Inclusive of GST |
$963 |
| Total fee payable by self-funded individual |
$107 |
This support is in addition to wage support provided under the Job Support Scheme, announced at the Resilience and Solidarity Budgets.
For more information, please refer to the links above in “this course eligible for”.
Participants are eligible for IBF enhanced course fee subsidies up to 90%.
Eligible Individuals Include:
Programme(s) Commencing between 1 Jan 2022 till 30 Jun 2022
- Company-sponsored individuals or self-sponsored participants
- Singapore Citizens or Singapore Permanent Residents, physically based in Singapore
- Successfully completed IBF-STS recognized programme (Achieve min. 75% attendance and pass all assessment components)
Programme(s) Commencing between 1 Jan 2022 till 30 Jun 2022
For Singaporeans
below the age of 40 & Singapore Permanent Residents of all age groups
below the age of 40 & Singapore Permanent Residents of all age groups
| Data Analytics using Python Course Fee |
$1,000 |
| Add 7% GST |
$70 |
| Deduct Enhanced Funding Support (80%) – Not including GST |
$800 |
| Total fee payable by self-funded individual |
$270 |
For Singaporeans
Aged 40 and above
Aged 40 and above
| Data Analytics using Python Course Fee |
$1,000 |
| Add 7% GST |
$70 |
| Deduct Enhanced Funding Support (90%) – Not including GST |
$900 |
| Total fee payable by self-funded individual |
$170 |
TAG is available for training programmes commencing between 1 Jul 2021 and 30 Jun 2022 (both dates inclusive) and completed no later than 30 September 2022
| Training Allowance Grant (TAG) at $10 per training hour for eligible company-sponsored individuals (paid out after course completion) |
For completing this course $160 |
This support is in addition to wage support provided under the Job Support Scheme, announced at the Resilience and Solidarity Budgets.
For more information, please refer to the links above in “this course eligible for”.
- IBF Programme Code
- SkillsFuture Programme Code
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