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Conquer Data Science
With Python 

Course Price

RM 2,000

Duration: 5 days/40 hours

PROGRAMME HIGHLIGHTS

- 40 hours training
- 4-5 industry-related projects
- Experienced instructor
- Basic to intermediate level 

WHAT YOU WILL LEARN

- How to wrangle data, or Data wrangling
- Learning to explore data or Data exploration
- Visualising data
- Learning how to scrap data from various sources or datasets
- Fundamentals of Python programming 
- Data Science libraries 

OVERVIEW

This course is a 40 Hours curriculum intended for those who have a basic knowledge of python programming. In this course, we will learn the basics of conducting data science, how to perform data analysis in python and then create some beautiful visualizations using Python. This data science course also summarizes many concepts, techniques, and algorithms in machine learning, beginning with topics such as linear regression and ending up with three projects.

WHO SHOULD ENROLL

- Software Professionals
- IT Professionals
- Analytics professionals
- Data Scientist
- Data Analyst
- Fresh Graduates
- Anyone with a genuine interest in Data Science

COURSE BENEFITS

- Our aim is to provide everyone vital hands-on experience so that you are well-prepared for job interviews alongside an exhibition at their positions
- Learn from pioneers in Data Science, both in research and industry.
- Learn the tricks of the trade from seasoned Python Developer
practitioner.
- Work on hands-on projects that develop your ability to solve real-world problems.

- Practice your skills on our hands-on projects that simulate real-world problems

- How to wrangle data

- Learning to explore data

- Visualizing data

- Learning how data is scrapped from various datasets or sources

- Fundamentals of Python programming

COURSE HIGHLIGHTS

- 100 % Hands-on Training 
- 40 Hours Instructor-led Training 
- 3 Projects
- Certifications, videos and resources 
- Weekly assignments and assessments 
- Industry-relevant content

SKILLS YOU WILL LEARN

- Hands-on Exposure to Data Science 
- Work on real-world projects in Data Science 
- Create your own applications for data retrieval, processing, and visualization

KEY FEATURES

•           Comprehensive Blended Learning program

•           flexible access to online classes

•           instructions carried out through industry experienced trainers

•           Interactive Quizzes

•           15+ in-demand technologies and skills

•           Get hands on experience with four industry related projects

•           24x7 learner assistance and support

INQUIRY PROCESS

The inquiry process consists of three simple steps.

•STEP 1 Submit Inquiry- Tell us a bit about yourself and the questions you want to enquire

•STEP 2 Reviewing – Your questions will be processed and answered within a day or two 

•STEP 3 Response – Answers will typically be sent through email. However, you may tell us the option you prefer us to contact you in

COURSE MODE

•           Physical Classroom Training (Malaysia)

•           On-site Company Training (Malaysia)

•           Online Training via Microsoft Team (Malaysia and International)

COURSE FEE

The admission fee for this Data Science with Python certification program is RM2,000.

Duration: 13 days/40 hours

COURSE HIGHLIGHTS

- 4 hours of Python Tutorial Beginner Kit contains of pre recorded video       on basics of python programming
- 40 Hours of Hands-On Practice
- 40 Hours of Assignments
- 6  Industry Relevant Projects
  Certifications , Videos and Resources
- Weekly assignments and assessments

FAQ

Is this course beginner friendly?

Yes, it is 

Do you need programming background to learn data science?

No, you don’t need as we will cover necessary Python fundamentals during your learning with us.

What is Data Science with Python course?

This Data Science with Python course is the perfect stepping stone to venture into becoming an aspiring data scientist. It is interesting because in this 40 hours course, you will have an understanding on necessary data analytics tools and techniques, data visualisation, introduction to Python & data science libraries, the famous web scrapping techniques and many more!

Can I become a data scientist after completing this course?

Absolutely Not. It takes time, practice and experience to become one. However, with this course and all the hands-on projects will give you real time analytics experience used in industries, sufficient for you to start preparing for job interviews. 

Which is the best data science with Python training company in Malaysia?

Nexperts Academy is the best in Malaysia. Our google rating is an evident of our strength in this field.

Will I receive a certificate upon finishing this course?

Yes, you will get a personalized digital certificate downloadable as a PDF. You will need to complete over 85% of the curriculum lessons

DATA SCIENCE WITH PYTHON

Module Structure

Day 1, Day 2, Day 3
1.    Lesson 01 - Data Science Overview Introduction to Data Science Different Sectors Using Data Science Purpose and Components of Python
   
2.    Lesson 02 - Data Analytics Overview
Data Analytics Process Knowledge Check
Exploratory Data Analysis(EDA) EDA-Quantitative Technique EDA -Graphical Technique
Data Analytics Conclusion or Predictions Data Analytic s Communication
Data Types for Plotting Data Types and Plotting

3.    Lesson 03- Statistical Analysis and Business Application
Introduction to Statistics
Statistical and Non- statistical Analysiss Major Categories of Statistics Statistical Analysis Considerations Data Distribution
Dispersion
Knowledge Check Histogram Testing
Correlation and Inferential Statistics

4.    Lesson 04 -Python Environment Setup and Essentials
Anaconda
Installation of Anaconda Python Distribution (contd.) Data Types with Python
Basic Operators and Functions
   
5.    Lesson 05 - Mathematical Computing with Python (NumPy)
Introduction to NumPy Activity-Sequence it Right
Demo 01- Creating and Printing and narray
Knowledge Check Class and Attributes of ndarray Basic Operations
Activity-Slice It Copy and Views
Mathematical Functions of NumPy Mathematical Functions of NumPy

6.    Lesson 06 - Scientific computing with Python (SciPy)
Introduction to SciPy
SciPy Sub Package - Integration and Optimization Knowledge Check
SciPy sub package
Demo - Calculate Eigenvalues and Eigenvector Knowledge Check
SciPy Sub Package - Statistics, Weave and IO Solving Linear Algebra problem using SciPy Assignment 01 Demo
Perform CDF and PDF using Scipy

Day 4 & Day 5
7.    Lesson 07 - Data Manipulation wit h Pandas
Introduction to Pandas

Knowledge Check Understanding Data Frame View and Select Data Demo Missing Values
Data Operations Knowledge Check
File Read and Write Support Knowledge Check- Sequence it Right Pandas Sql Operation
Analyze the Federal Aviation Authority Dataset using Pandas
Assignment 01 Demo
Analyze New York city fire department Dataset

8.    Lesson 08 - Machine Learning with Scikit–Learn
Machine Learning Approach Steps One and Two
Steps Three and Four How it Works
Steps Five and Six
Supervise d Learning Model Consideration s Scikit Learn
Supervised Learning Models- Linear Regression
Supervised Learning Models- Logistic Regression Unsupervised Learning Models
Pipeline
Model Persistence and Evaluation Knowledge Check
Analyzing Ad Budgets for different media channels
Pipeline
Model Persistence and Evaluation Knowledge Check

0Assignment One
Building a model to predict Diabetes

9.    Lesson 09 - Natural Language Processing with Scikit Learn
NLP Overview NLP Applications Knowledge Check
NLP Libraries- Scikit Extraction Consideration s
Scikit Learn- Model Training and Grid Search
Analyzing Spam Collection Data Demo
Assignment 01
Sentiment Analysis using NLP

10.    Lesson 10 - Data Visualization in Python using Matplotlib
Introduction to Data Visualization Knowledge Check
Line Properties
(x,y) Plot and Subplots Knowledge Check Types of Plots
Draw a pair plot using seaborn library Assignment 01 Demo
Analysing Cause of Death


11.    Lesson 11 - Web Scraping with Beautiful Soup
Web Scraping and Parsing Knowledge Check
Understanding and Searching the Tree

Demo3 Navigating a Tree Knowledge Check Modifying the Tree
Parsing and Printing the Document Web Scraping of any Website

12.    Lesson 12 - Python integration with Hadoop Map Reduce and Spark
Why Big Data Solutions are Provided for Python Hadoop Core Component s
Python Integration with HDFS using Hadoop Streaming
Demo 01 - Using Hadoop Streaming for Calculating Word Count Knowledge Check
Python Integration with Spark using PySpark
Demo 02 - Using PySpark to Determine Word Count Knowledge Check
Determine the word count
Assignment 01 Demo
Display all the airports based in New York using PySpark

Objectives / What You Will Learn
Explore Python fundamentals, including basic syntax, variables, and types Create and manipulate regular Python lists
Use functions and import packages
Build NumPy arrays, and perform interesting calculations Create and customize plot son real data
Supercharge with control flow, and get to know the Pandas Data Frame
Use Python to read And write files Illustrate Supervise d Learning Algorithm s
Identify and recognize machine learning algorithms around us

Outline Course
DURATION : 5 Days
TIMING    : 9.00 am – 5.00pm
DURATION : 40 hours

Outcomes
Data wrangling Data exploration Data visualization
Mathematical computing
Web scraping Hypothesis building
Python programming concepts NumPy and SciPy package
Scikit Lear n package for Natural Language Processing


 

WHY NEXPERTS ACADEMY

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- CERTIFIED TRAINERS

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- LIFETIME ACCESS TO
RECORDED SESSIONS

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- HIGHLY EXPERIENCED
WITH INTERVIEW PREPARATION

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- FLEXIBLE SCHEDULE

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- 24/7 SUPPORT

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- ONE ON ONE ASSISTANCE