Course Overview
Python for Data Scientists is a course that offers a hands-on approach to gain an entry-level understanding of data analytics tools and techniques for scientific and mathematical computing by using Python. You will learn how to complete real-world tasks such as data analysis and visualization, as well as gain a fundamental understanding of machine learning algorithms. Through lectures and lab exercises, the concepts will be reinforced, and upon completion of the course, you will have the skills to apply Python to complete real-world tasks.
Course Objective
Who should get certified:
Prerequisites:
Course Curriculum
- Getting to know the participants
- Introduction to PMI®
- PMP® Certification – advantages
- PMP® Certification – process and fees related information
- PMP ® Application procedures – instructions on how to fill in the form
- PMP® examination – information on the split of questions, question pattern
- PMP® examination – tips on how to prepare and take the examination (this theme will be reiterated throughout the course)
- PMP® – fulfilling the CCR requirements
- Familiarization with the course outline
- Familiarization with the protocols and timings
- Expectation setting and clarifications
- Introductory quiz – to assess the current level of familiarization of the participants with PMBOK® concepts and assess the gaps
- Using variables:
- Python keywords
- Built-in string functions in Python
- Single quote for string literals
- Triple quote for string literals
- Python raw strings
- Unicode literals
- Operators and expressions
- Convert among types
- Write unicode characters
- Formatted unicode string literals
- Legacy codes in string formatting
- Command line parameters
- Reading keyboard input
- About control flow
- What’s with the white space
- If and Elif control flow statements
- Conditional statements
- Relational and Boolean operators
- While loops
- Alternate ways to exit from a loop
About Sequences Lists Tuples:
- Indexing and slicing
- Iterating through a sequence
- Functions for all sequences
- The enumerate() function
- Operators and keywords for sequences
- The xrange() function
- Nested sequences
- List comprehensions
- Generator expressions
Python files I/O:
- File open
- The with block
- Read text files
- Writing to text files
- About dictionaries:
- When to use dictionaries
- Create dictionaries
- Python dictionary get()
- Iterate through a dictionary:
- Read a file data into a dictionary
- Count with dictionaries
- About sets:
- Create a set
- Work with sets
- Define a function
- Function parameters
- Global variables
- Variable scope
- Return values
- Try-except
- Multiple exceptions handling
- Generic exceptions handling
- Ignore an exception
- Using else clause:
- Cleaning up with finally
- Re-raise an exception
- Raise a new exception
- The standard exception class hierarchy
- The OS module
- Environment variables
- Launch external processes:
- Paths, directories, and file names
- Walking directory trees
- Dates and times
- Send an e-mail
- The Zen of Python
- Common Python idioms
- Packing and unpacking
- Lambda functions
- List comprehensions
- Generators vs. iterators
- Generator expressions
- String tricks
- What is a module?
- The import statements
- Where did the .pyc file come from?
- The module search path
- Tab completion
- Zipped libraries
- Create modules
- Packages
- Module aliases
- Batteries not included
- Define classes
- Instance objects
- Instance attributes
- Methods
- The __init__ method
- Properties
- Class data
- Inheritance
- Multiple Inheritance
- Base classes
- Special methods
- Pseudo-private variables
- Static methods
- Program development
- Comments
- Pylint
- Customizing Pylint
- Unit testing
- The unittest module
- Create a test class
- Establish success or failure
- Startup and Cleanup
- Run the tests
- Debugging
- Start the debug mode
- Step through a program
- Set breakpoints
- Debug a command reference
- Benchmarking
- About XML
- Normal approaches to XML
- Which module to use?
- Get started with ElementTree
- How ElementTree works
- Create a new XML Document
- Parse XML Documents
- Navigate the XML Documents
- Use XPath
- Advanced XPath
- Features of iPython
- Start iPython
- Tab completion
- Magic commands
- Benchmarking
- External commands
- Enhanced help
- Notebooks
- Python’s scientific stack
- NumPy overview
- Create arrays
- Create ranges
- Work with arrays
- Shapes
- Slicing and indexing
- Indexing with Booleans
- Stacking
- Iterating
- Tricks with arrays
- Matrices
- Data types
- NumPy functions
- About SciPy
- Polynomials
- Vectorize functions
- Sub-packages
- Get help
- Weave
- Clustering package
- Constants
- Legacy discrete Fourier transforms
- Integration and ODEs
- Interpolation
- Input and output
- Linear algebra
- Multidimensional image processing
- Orthogonal distance regression
- Optimization and root finding
- Signal processing
- Sparse matrices
- Spatial algorithms and data structures
- Special functions
- Statistical functions
- About Pandas
- Pandas
- Architecture
- Series
- DataFrames
- Data alignment
- Index objects
- Basic indexing
- Broadcasting
- Remove entries
- Time series
- Read data
- About Matplotlib
- Matplotlib architecture
- Matplotlib terminology
- Matplotlib keep state
- What else can you do?
- Image file types supported by PIL
- The image class
- Read and write
- Create thumbnails
- Coordinate system
- Crop and paste
- Rotate, resize, and flip
- Enhance
Corporate Benefits
By upskilling your employees in Python for Data Scientist training, you can:
HRD Corp Claimable
We are proud to be an authorized training provider of HRD Corp (Human Resources Development Corporation). Our certification training programs are eligible for funding under SBL-Khas Scheme.
HRD Corp provides training and upskilling opportunities for Malaysian employees who are:
- Malaysian citizens or permanent residents
- Employed in a company that contributes to HRD Corp (employer with 10 or more Malaysian employees, or employers from specific sectors)
- Registered with the HRD Corp portal and have an activated account
- Have not attended the same training program within the last 12 months
- Meet the specific requirements for the training program, such as qualifications, skills, or job-specific criteria.
Our dedicated team will help you every step of the way, from claim application to completion. Invest in your employees’ professional growth and development by enrolling them in our training today!
Testimonials
Testimonials
FAQs
Obtaining Python for Data Scientist certification can demonstrate your expertise in the field, increase your job opportunities and advancement potential, help you stand out in a competitive job market, and lead to potential career advancement and professional development opportunities.
It is sufficient for a student to have a basic understanding of programming concepts and math.
The course will require a computer with Python installed and a text editor or integrated development environment (IDE). The course also requires some specific libraries such as NumPy, Pandas, and scikit-learn.
Yes, you will receive a certificate to prove that you have completed your training.
There is currently no examination available for this course.
HRD Corp Claimable Course is a dedicated programme that provides funding and support to registered employers for employee retraining and upskilling in accordance with operational and business requirements.
To apply for this course under the HRD Corp programme, please fill out the form above, and our personnel will contact you personally.
To make a claim, your company must first be registered with HRD Corp and have contributed. After the training is completed, your company must submit a claim form to HRD Corp along with supporting documentation. There is no need to pay anything up front. HRD Corp will then process the claim and, if approved, reimburse you.
Our personnel will walk you through the entire claim application process from beginning to end.
Following your registration, our personnel will contact you to provide consultation, advice, and feedback. You can get in touch with the person in charge, or you can reach us at info@newhorizons.my. We are always happy to help.
