Data Science With Python Certification

It will help you master important Python programming concepts such as data operations, file operations, object-oriented programming, and various Python libraries such as Pandas, Numpy, and Matplotlib essential for Data Science.

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Data Science With Python Certification Course Training

Who this course is for:

Analysts or BI professionals looking for a deep introduction to basic Python.
Aspiring data scientists who want to build foundational Python programming skills.

Anyone interested in learning one of the most popular open source programming languages in the world.
Students looking to learn powerful, practical skills with hands-on projects and course demos.

What you will Learn:

Master the building blocks of base Python, including data types, variables, loops, functions and more.

Learn how to use Jupyter Notebooks to write, manage, and comment your Python code

Analyze and manipulate numeric data, text strings, lists, tuples, dictionaries and sets.
Explore raw data using conditional logic, nested loops, custom functions, and comprehensions.

Use Python's Openpyxl package to read & write data to Excel worksheets.
Build solid, foundational Python skills for data analysis & business intelligence

Course Benefits & Key Features

Python Programming Certification Course’s benefits and key features.

Modules

30+ Modules.

Lessons

80+ Lessons

Practical

40+ Hands-On Labs

Life Projects

5+ Projects

Resume

CV Preparations

Job

Jobs Reference

Recording

Session Recording

Interviews

Mock Interviews

Support

On Job Supports

Membership

Membership Access

Networks

Networking

Certification

Certificate of Completion

INSTRUCTOR-LED LIVE ONLINE CLASSES

Our learn-by-building-project method enables you to build

practical or coding experience that sticks. 95% of our

learners say they have confidence and remember more

when they learn by building real world projects which is

required to work in your real life.

Get step-by-step guidance to practice your skills without getting stuck
Validate your technical problem-solving skills in a real environment
Troubleshoot complex scenarios to practice what you learned
Develop production experience that translates into real-world

.

Data Science with Python Certification Course Job Outlook

.

Ranked #1 Programming
Language

TIOBE and PYPL ranks Python as the most popular global programming language.

Python Salary
Trend

The average salary for a Python Developer is $114,489 per year in the United States.

44.8% Compound annual growth rate (CAGR)

The global python market size is expected to reach USD 100.6 million in 2030.

Python Developer
Data Analyst

Python Data Scientist

Job Titles include:

Data Scientist
AI Engineer

AI Researcher
Machine Learning Engineer

Data Science with Python Tools Covered

.

Data Science with Python Skills Covered

.

Python Programming
Supervised and Unsupervised Machine Learning

Statistical Foundations
Database Integration with Python

Data Analysis and Visualization
Data Visualization Using Tableau

Why Data Science With Python Certification Course?

Learn In-demand Skills

Those with careers in data analysis learn relevant in-demand skills that span industries and add value to every digital-enabled organization.

Earn a Higher Salary

Experienced data analysts can earn up to $112,000 per year and transition into higher-paying jobs as Senior Data Analysts, Data Scientists, or Analytics Managers.

Positive Job Outlook

The data analytics market is predicted to hit $132.90 Billion USD by 2026. COVID-19 pandemic accelerated the adoption of data analytics solutions and services.

Shape the Future

Data analysts transform organizations by capitalizing on data to improve their business decisions and solve critical real-world problems.

Become a Leader

Being a central part of an organization’s decision-making processes, analytics experts often pick up strong leadership skills as well.

Data Analysis are Constantly Evolving

Data analysis moves quickly, and data analysts are constantly learning and advancing in their careers.

GreaterHeight Certificates holders are prepared to work at companies like these.

Some Alumni Testimonies

Investing in the course "Become a Data Analyst" with GreaterHeight Academy is great value for the money and I highly recommend. The trainer is very knowledgeable, very engaging, provided us with quality training sessions on all courses and was easily acessible for queries. We also had access to the course materials and also the timely availability of the recorded videos made it easy and aided the learning process..

QUEEN OBIWULU

Team Lead, Customer Success

The training was fantastic, the instructor is an awesome lecturer, relentless and not tired in his delivery. He obviously enjoys teaching, it comes natural to him. We got more than we expected. He extended my knowledge of Excel beyond what I knew, and the courses were brilliantly delivered. They reach out, follow up, ask questions, and in fact the support has been great. They are highly recommended and I would definitely subscribe to other training programs from them.

BISOLA OGUNRO

Fraud Analytics Risk Oversight Manager

It's one thing to look for just a Data Analysis training, and it's another to get the knowledge transferred through certified professional trainers. No matter your initial level of proficiency in any of the Data Analysis tools, GreaterHeight Academy would meet you there and take you up to a highly proficienct and confident level in a short time at a reasonable pace. I learnt a lot of Data Analysis tools and skills at GreaterHeight from patient and resourceful teachers.

TUNDE MEREDITH

Operation Director - Abbfem Technology

The Data Analysis training program was one of the best I have attended. The way GreaterHeight took off with Excel and concluded the four courses with Excel was a mind blowing - it was WOW!! I concluded that I'm on the right path with the right mentor to take me from a novice to professional. GreaterHeight is the best as far as impacting Data Analysis knowledge is concern. I would shout it at the rooftop to recommend GreaterHeight to any trainee that really wants to learn.

JOHN OSI PETER

Greaterheight

I wanted to take a moment to express my deepest gratitude for the opportunity to study data analytics at GreaterHeight Academy. I am truly impressed by the level of dedication and support that the sponsor and CEO have put into this program. GreaterHeight Academy is without a doubt the best tech institution out there, providing top-notch education and resources for its students. One of the advantages of studying at GreaterHeight Academy is the access to the best tools and technologies in the field.

AYODELE PAYNE

Sales/Data Analyst

It is an unforgettable experience that will surely stand the test of time learning to become a Data Analyst with GreaterHeights Academy. The Lecture delivery was so impactful and the Trainer is vast and well knowledgeable in using the applicable tools for the Sessions. Always ready to go extra mile with you. The supports you get during and after the lectures are top notch with materials and resources available to build your confidence on and off the job.

ADEBAYO OLADEJO

Customer Service Advisor (Special Operations)

Data Science With Python Certification Course

GreaterHeight Academy's Data Science with Python Certification Course is designed to help you master Data Science with Python Programming language. It will help you master important Python programming concepts such as data operations, file operations, object-oriented programming, and various Python libraries such as Pandas, Numpy, and Matplotlib essential for Data Science. This course is well-suited for professionals and beginners. This training will introduce you to different types of Machine Learning, Recommendation Systems, and other relevant concepts to kickstart your Data Science career.

WEEK 4-7 | 19 Modules | 20+ Hours | 18 Skills

Course Modules

Overview of Python
The Companies using Python
Different Applications where Python is Used
Discuss Python Scripts on UNIX/Windows
Values, Types, Variables
Operands and Expressions
Conditional Statements
Loops
Command Line Arguments
Writing to the Screen
What is Data Science?
What does Data Science involve?
Era of Data Science
Business Intelligence vs Data Science
Life cycle of Data Science
Tools of Data Science

Hands-on:

Creating “Hello World” code
Variables
Demonstrating Conditional Statements
Demonstrating Loops

Data Analysis Pipeline
What is Data Extraction?
Types of Data
Raw and Processed Data
Data Wrangling
Python files I/O Functions
Numbers
Strings and related operations
Tuples and related operations
Lists and related operations
Dictionaries and related operations
Sets and related operations

Hands-on:

Tuple - properties, related operations, compared with the list
List - properties, related operations
Dictionary - properties, related operations
Set - properties, related operations

Functions
Function Parameters
Global Variables
Variable Scope and Returning Values
Lambda Functions
Object Oriented Concepts
Standard Libraries
Modules Used in Python
The Import Statements
Module Search Path
Package Installation Ways
Errors and Exception Handling
Handling Multiple Exceptions

Hands-on:

Lambda function in Python
Errors and Exceptions in Python
Packages and Modules in Python
Functions - Syntax, Arguments, Keyword Arguments, Return Values
Sorting - Sequences, Dictionaries, Limitations of Sorting

Data Analysis
NumPy - arrays
Operations on arrays
Indexing, slicing, and iterating
Reading and writing arrays on files
Pandas - data structures & index operations
Reading and Writing data from Excel/CSV formats into Pandas
Metadata for imported Datasets
Matplotlib library
Grids, axes, plots
Markers, colors, fonts, and styling
Types of plots - bar graphs, pie charts, histograms
Contour plots

Hands-on:

NumPy library - Creating NumPy array, operations performed on NumPy array
Pandas library - Creating series and data frames, Importing and exporting data
Matplotlib library - Using Scatterplot, histogram, bar graph, a pie chart to show information, Styling of Plot

Data Manipulation
Basic Functionalities of a data object
Merging of Data objects
Concatenation of data objects
Types of Joins on data objects
Exploring and analyzing datasets
Analysing a dataset

Hands-on:

Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples(), GroupBy operations, Aggregation, Concatenation, Merging and joining

What is Machine Learning?
Machine Learning Use-Cases
Machine Learning Process Flow
Machine Learning Categories
Linear regression
Gradient descent

Hands-on:

Linear Regression – Boston Dataset

What are Classification and its use cases?
What is a Decision Tree?
Algorithm for Decision Tree Induction
Creating a Perfect Decision Tree
Confusion Matrix
What is Random Forest?

Hands-on:

Implementation of Logistic Regression, Decision Tree, Random Forest algorithms

Introduction to Dimensionality
Why Dimensionality Reduction
PCA
Factor Analysis
Scaling dimensional model
LDA

Hands-on:

Implementing PCA
Scaling dimensional model
Implementing LDA

What is Naïve Bayes?
How Naïve Bayes works?
Implementing Naïve Bayes Classifier
What is a Support Vector Machine?
Illustrate how Support Vector Machine works
Hyperparameter Optimization
Grid Search vs. Random Search
Implementation of Support Vector Machine for Classification

Hands-on:

Implementation of Naïve Bayes, SVM algorithms

What is Clustering & its Use Cases?
What is K-means Clustering?
How does the K-means algorithm works?
How to do optimal clustering
What is C-means Clustering?
What is Hierarchical Clustering?
How does Hierarchical Clustering work?

Hands-on:

Implementing K-means Clustering
Implementing Hierarchical Clustering

What are Association Rules?
Association Rule Parameters
Calculating Association Rule Parameters
Recommendation Engines
How do Recommendation Engines work?
Collaborative Filtering
Content-Based Filtering

Hands-on:

Implementing Apriori Algorithm
Performing Market Basket Analysis

What is Reinforcement Learning?
Why Reinforcement Learning?
Elements of Reinforcement Learning
Exploration vs. Exploitation dilemma
Epsilon Greedy Algorithm
Markov Decision Process (MDP)
Q values and V values
Q – Learning
Values

Hands-on:

Calculating Reward
Discounted Reward
Calculating Optimal quantities
Implementing Q Learning
Setting up an Optimal Action

What is Time Series Analysis?
Importance of TSA
Components of TSA
White Noise
AR model
MA model
ARMA model
ARIMA model
Stationarity
ACF & PACF

Hands-on:

Checking Stationarity
Converting non-stationary data to stationary
Implementing Dickey-Fuller Test
Plotting ACF and PACF
Generating the ARIMA plot

What is Model Selection?
Need for Model Selection
Cross Validation
What is Boosting?
How do Boosting Algorithms work?
Types of Boosting Algorithms
Adaptive Boosting

Hands-on:

Performing Cross Validation
Implementing AdaBoost using Python

What is Exploratory Data Analysis?
EDA Techniques
EDA Classification
Univariate Non-graphical EDA
Univariate Graphical EDA
Multivariate Non-graphical EDA
Multivariate Graphical EDA
Heat Maps

Hands-on:

Implementing Graphical EDA Techniques
Implementing Non-Graphical EDA Techniques

Basics of database management
Python SQL Server
Create database
Create a table
Insert into table
Select query
Where clause
OrderBy clause
Delete query
Drop table
Update query
Limit clause
Join and Self-Join
MongoDB (Unstructured)
Insert_one query
Insert_many query
Update_one query
Update_many query
Create_index query
Drop_index query
Delete and drop collections
Limit query

Hands-on:

CRUD operations using Python SQL Server and MongoDB

Data Visualization
Business Intelligence tools
VizQL Technology
Connect to data from the File
Connect to data from the Database
Basic Charts
Chart Operations
Combining Data
Calculations

Hands-on:

Connecting to data from File, Database, and Server
Performing operations on Hierarchies, Data Granularity and Highlighting feature
Creating calculated fields using basic functions
Defining LOD expressions
Creating Parameters
Performing User Input and What-if analysis

Trend lines
Reference lines
Forecasting
Clustering
Geographic Maps
Using charts effectively
Dashboards
Story Points
Visual best practices
Publish to Tableau Online

Hands-on:

Analyzing data using techniques including Forecasting, Trend Lines, Reference Lines, Clustering, and Geographic Maps
Building Dashboard Layout and Formatting
Building Story points

Predict the species of Plant

Hands-on:

Analyze the data
Predict the plant species

DATA SCIENCE WITH PYTHON CERTIFICATION COURSE COST

United States

$349.99

United Kingdom

£299.99

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Python Programming Certification Course Trainng

GreaterHeight Academy's Data Science with Python Certification Training teaches you the significance of data science, machine learning, and its application in Python. This course helps you gain proficiency in automating real-world scenarios with machine learning algorithms.
GreaterHeight Academy offers the most exceptional Data Science with Python training if you are dedicated to becoming proficient in Python.
Seize the opportunity and enroll in Data Science with Python Certification Course now to benefit from the teaching of industry experts. Elevate your Python skills with us today.

The prerequisites for GreaterHeight Academy's Python for Data Science Course include a fundamental understanding of Computer Programming Languages.

Python is one of the premier, flexible, and powerful open-source languages that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, It has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. It's continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple-to-read syntax and easy compilation feature. The debugging program is a breeze in Python, and it has a built-in debugger. It has evolved as the most preferred Language for Data Analytics. The increasing search trends also indicate that it is the Next Big Thing and a must for Professionals in the Data Analytics domain.

After completing this Data Science with Python Certification course, you will be able to:

Programmatically download and analyze data
Learn techniques to deal with different types of data – ordinal, categorical, encoding
Learn data visualization
Using python notebooks, master the art of presenting step-by-step data analysis
Gain insight into the 'Roles' played by a Machine Learning Engineer
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Explain Time Series and its related concepts
Perform Text Mining and Sentiment analysis GreaterHeight Academy offers the best course for Python data science and ML.

Enroll now in our Data Science with Python training and get a chance to learn from industry leaders.

Freshers, Programmers, Developers, Technical Leads, Architects
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
Professionals who want to design automatic predictive models

The duration of the Data Science with Python Course is approximately 5 to 10 weeks. Depending on their experience with web development, data science, and other related fields, it may vary from person to person.

The Data Science with Python course fee is INR 21995, but you can get it at a discounted price of INR 19795. You can get 10% OFF and save 2200. No Cost EMI Starts at 6,599 / month.

Here is the list of topics covered in the Data Science with Python Course Syllabus:

Introduction to Data Science and ML using Python
Data Handling, Sequences and File Operations
Deep Dive – Functions, OOPs, Modules, Errors, and Exceptions
Introduction to NumPy, Pandas, and Matplotlib
Data Manipulation
Introduction to Machine Learning with Python
Supervised Learning - I
Dimensionality Reduction
Supervised Learning - II
Unsupervised Learning
Association Rules Mining and Recommendation Systems
Reinforcement Learning
Time Series Analysis
Model Selection and Boosting
Statistical Foundations
Database Integration with Python
Data Connection and Visualization in Tableau
Advanced Visualizations
In-Class Project

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Data Science With Python Certification

Data Science With Python Certification Course Training

Course Benefits & Key Features

Python Programming Certification Course’s benefits and key features.

Modules

Lessons

Practical

Life Projects

Resume

Job

Recording

Interviews

Support

Membership

Networks

Certification

INSTRUCTOR-LED LIVE ONLINE CLASSES

Data Science with Python Certification Course Job Outlook

Ranked #1 ProgrammingLanguage

Python SalaryTrend

44.8% Compound annual growth rate (CAGR)

Job Titles include:

Data Science with Python Tools Covered

Data Science with Python Skills Covered

Why Data Science With Python Certification Course?

Learn In-demand Skills

Earn a Higher Salary

Positive Job Outlook

Shape the Future

Become a Leader

Data Analysis are Constantly Evolving

GreaterHeight Certificates holders are prepared to work at companies like these.

Some Alumni Testimonies

QUEEN OBIWULU

BISOLA OGUNRO

TUNDE MEREDITH

JOHN OSI PETER

AYODELE PAYNE

ADEBAYO OLADEJO

Data Science With Python Certification Course

Module 1: Introduction to Data Science and ML using Python

Module 2: Data Handling, Sequences and File Operations

Module 3: Deep Dive – Functions, OOPs, Modules, Errors, and Exceptions

Module 4: Introduction to NumPy, Pandas, and Matplotlib

Module 5: Array Manipulation using NumPy

Module 6: Introduction to Machine Learning with Python

Module 7: Supervised Learning - I

Module 8: Dimensionality Reduction

Module 9: Supervised Learning - II

Module 10: Unsupervised Learning

Module 11: Association Rules Mining and Recommendation Systems

Module 12: Reinforcement Learning

Module 13: Time Series Analysis

Module 14: Model Selection and Boosting

Module 15: Statistical Foundations

Module 16: Database Integration with Python

Module 17: Data Connection and Visualization in Tableau

Module 18: Advanced Visualizations

Module 19: In-Class Project

DATA SCIENCE WITH PYTHON CERTIFICATION COURSE COST

United States

United Kingdom

Career and Certifications

Our Advisor is just a CALL away

+1 5169831065 +447474275645

Available 24x7 for your queries

Talk to our advisors

Python Programming Certification Course Trainng

About Data Science with Python Certification Course

What are the prerequisites for this Data Science with Python Course?

Why Learn Python for Data Science?

What are the objectives of our Data Science with Python Course?

Who should go for this Python for Data Science course?

What is the Data Science with Python Course duration?

What is the Data Science with Python Course fee?

What topics are covered in Data Science with Python course syllabus?

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