Python Certification Training For Data Science

Select your preferred delivery method

Choose a location/time


Description

Python Certification Training for Data science course helps you gain expertise in Quantitative Analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role. You will use libraries like Pandas, Numpy, Matplotlib, Scikit and master the concepts like Python Machine Learning Algorithms such as Regression, Clustering, Decision Trees, Random Forest, Naïve Bayes and Q-Learning and Time Series. Throughout the Course, you’ll be solving real-life case studies on Media, Healthcare, Social Media, Aviation, HR and so on. Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. 

 

Our Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds. 

 

After completing this Data Science Certification training, 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 I 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 Sentimental analysis
  • Gain expertise to handle business in future, living the present

It's continued to be a favourite 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. Debugging programs is a breeze in Python with its built in debugger. It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. It has evolved as the most preferred Language for Data Analytics and the increasing search trends on Python also indicates that it is the "Next Big Thing" and a must for Professionals in the Data Analytics domain.

 

You will also understand Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms. This course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master the concepts like Python machine learning, scripts, and sequence.

Data Science certification course in Python is a good fit for the below professionals:

  • 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
  • 'Python' professionals who want to design automatic predictive models

The pre-requisites for this Python course include the basic understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, you will be provided with complimentary “Python Statistics for Data Science” as a self-paced course once you enroll for the course.

DROP A QUERY

Agenda

  • 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
  • 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
  • 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
  • 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
  • matplotlib library
  • Grids, axes, plots
  • Markers, colours, fonts and styling
  • Types of plots - bar graphs, pie charts, histograms
  • Contour plots
  • Basic Functionalities of a data object
  • Merging of Data objects
  • Concatenation of data objects
  • Types of Joins on data objects
  • Exploring a Dataset
  • Analysing a dataset
  • Python Revision (numpy, Pandas, scikit learn, matplotlib)
  • What is Machine Learning?
  • Machine Learning Use-Cases
  • Machine Learning Process Flow
  • Machine Learning Categories
  • Linear regression
  • Gradient descent
  • What are Classification and its use cases?
  • What is Decision Tree?
  • Algorithm for Decision Tree Induction
  • Creating a Perfect Decision Tree
  • Confusion Matrix
  • What is Random Forest?
  • Introduction to Dimensionality
  • Why Dimensionality Reduction
  • PCA
  • Factor Analysis
  • Scaling dimensional model
  • LDA
  • What is Naïve Bayes?
  • How Naïve Bayes works?
  • Implementing Naïve Bayes Classifier
  • What is Support Vector Machine?
  • Illustrate how Support Vector Machine works?
  • Hyperparameter Optimization
  • Grid Search vs Random Search
  • Implementation of Support Vector Machine for Classification
  • What is Clustering & its Use Cases
  • What is K-means Clustering
  • How does K-means algorithm work
  • How to do optimal clustering
  • What is C-means Clustering
  • What is Hierarchical Clustering
  • How Hierarchical Clustering works
  • What are Association Rules?
  • Association Rule Parameters
  • Calculating Association Rule Parameters
  • Recommendation Engines
  • How does Recommendation Engines work?
  • Collaborative Filtering
  • Content-Based Filtering
  • 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
  • α values
  • What is Time Series Analysis?
  • Importance of TSA
  • Components of TSA
  • White Noise
  • AR model
  • MA model
  • ARMA model
  • ARIMA model
  • Stationarity
  • ACF & PACF
  • What is Model Selection?
  • The need for Model Selection
  • Cross-Validation
  • What is Boosting?
  • How Boosting Algorithms work?
  • Types of Boosting Algorithms
  • Adaptive Boosting

Certification & Exam

Once you are successfully through the project (reviewed by an expert), you will be awarded with Python for Data Science Professional Certificate.

Why Us

We are here to ensure you get heard 24/7, and to take care of every single questions and doubts you have. Our dedicated support team will provide you best in class round the clock customer support. Superior customer service is the hallmark of our company and we always go the extra mile to satisfy each of our customers whether an individual or a corporate client.

FREQUENTLY ASKED QUESTIONS


Please click on the "ENROLL" button against the course you wish to enroll for. You need to provide your details (Name, Email ID, etc) and pay the course fee.

Payments can be made using global payment gateways such as PayPal and Stripe. Indian customers can pay using CCAvenue or PayUmoney.

You can register and pay for a course online with most of the major Credit or Debit Cards.

Yes, we do offer additional discounts to group and corporate training customers. Please get in touch with us by email (support@encertify.com) to find out more about our group discount offerings.

Use the "Drop a query"section in this page or check "Contact Us" section. Alternatively, please send an email to support@encertify.com to find out more about our course offerings.

We strongly recommended to continue with one mode of training for better learning experience. However, in case situation demands, you can switch mode of training upon availability of respective courses with other training modes. Check with our team well in advance for any change request to avoid logistics and operational inconvenience.

If you're between jobs and have been unemployed for last the 6 months, or you're a student taking a course for career growth, we do provide additional discounts for you on selected courses. Please email support@encertify.com to avail this benefit and discount coupon.

Note: These discounts are available on selected courses, have a limited number and on a first-come-first-serve basis.

Yes, we do provide additional discounts for military veterans on selected courses. Please email support@encertify.com for more details.

Firstly, we recommend you to check your spam folder, since the confirmation emails land up in spam sometimes. If you have not received any email on payment confirmation, or respective course details even in your spam folder, please email support@encertify.com for a quick resolution.

Customers Also Bought


Apache Spark and Scala Certification Training

Apache Cassandra Certification Training

AWS Architect Certification Training

Big Data Hadoop Certification Training

DevOps Certification Training

Have a question or need a custom quote?

In case you have a question or need a custom quote for any specific training, please email support@encertify.com , or leave a call back number with a message by clicking on "Request a Callback" from the footer section below.

Encertify Rating
4.5 out of 5 (15851 votes)