Expert Data Science with Python Training in Bangalore
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Data Science With Python Training in Bangalore

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08:00 AM & 10:00 AM Batches

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Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session


Weekend Regular

(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session


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(Class 4:30Hr - 5:00Hrs) / Per Session

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Get Our Data Science With Python Course

  • Our comprehensive training program focuses on assisting candidates in achieving their dream job by providing guidance on tech careers, industrial training, and programming skills.
  • Our experienced tutors offer extensive support in understanding all aspects of Data Science with the Python program, covering beginner to advanced topics.
  • We provide interview preparation, mock interviews, real-world projects, and career guidance to enhance job prospects at top MNCs.
  • Highly professional real-time trainers deliver complete online training in Data Science With Python Course.
  • The Data Science with Python Certification Course equips learners with deep knowledge of data science methods, techniques, and analytical skills.
  • Upon completion of the Data Science with Python Online Course, learners receive industry-recognized certification.
  • Key concepts covered include Data Science, Python, Python Basic Data Types, Python Packages, Importing Data, Data Manipulation, Statistics Basics, Machine Learning, Supervised Learning, Unsupervised Learning, and Other Machine Learning Algorithms.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
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This is How ACTE Students Prepare for Better Jobs


Course Objectives

    The Python packages
  • NumPy
  • Pandas
  • Matplotlib
  • Scikit-learn
  • TensorFlow are commonly used in data analysis.
  • These libraries provide strong machine learning, data processing, analytics, and visualization capabilities.
  • A robust programming language that may be employed for data manipulation
  • Exploratory data analysis
  • Statistical modeling
  • Machine learning
  • Data visualization.
Python's library ecosystem's rich design, readability, and simplicity, as well as its widespread use in the data science community, make it a great way to learn data science Python offers extensive, community-supported data science learning resources stable, and job prospects for.
  • Easier integration with other tools
  • More usage by data scientists Python's flexibility
  • Simplicity allow them to create faster prototyping
  • More efficient implementations
  • Improved teamwork in data science teams.
    Real-world examples where Python is used in data science include,
  • Analyzing customer data to optimize marketing campaigns
  • Predicting stock market trends to inform investment decisions
  • Optimizing supply chain management to minimize costs
  • Data manipulation using libraries like Pandas, data visualization with Matplotlib and Seaborn, statistical analysis and hypothesis testing.
  • Machine learning algorithms such as linear regression and random forests, model evaluation techniques, and feature engineering.
The duration to complete a data science with Python training course can vary depending on the program format, ranging from a few weeks for intensive boot camps to several months for more in-depth programs. The duration also depends on the learners' prior knowledge, learning pace, and the depth of the curriculum.

Are there any prerequisites required to enroll in data science with the Python program?

While prerequisites for data science with Python training programs may vary, having a basic understanding of programming concepts, statistics, and mathematics can be beneficial. Familiarity with Python programming basics is helpful but not always required, as introductory modules often cover the fundamentals.

Do you offer any hands-on projects or practical assignments as part of the training?

  • Yes, most data science with Python training programs includes hands-on projects and practical assignments.
  • These provide learners with opportunities to apply their knowledge to real-world datasets, build machine-learning models, and gain practical experience in solving data science problems.

What are the career Prospects of data science with Python training?

  • Completing data science with Python training opens up a wide range of career opportunities.
  • Graduates can pursue roles such as data scientist, data analyst, machine learning engineer, business analyst, research scientist, or data consultant.
  • These roles are in demand across various industries, including finance, healthcare, technology, e-commerce, and marketing.

Do I need programming skills before pursuing data science training with Python?

While prior programming experience can be helpful, it is not always necessary to pursue data science with Python training as many programs offer introductory modules that cover the fundamentals for beginners.
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Python for Data Science Course: A Comprehensive Overview

Enroll in the ACTE Python for Data Science course to gain expertise in writing Python code and utilizing essential packages like SciPy, Matplotlib, Pandas, Scikit-Learn, and NumPy. This comprehensive online training, designed by industry professionals, equips you with the skills sought after by top MNCs. Through real-world projects and assignments, you'll enhance your career prospects and confidently apply your knowledge to solve business challenges, including working with large-scale systems like Hadoop and Spark.

Additional Info

Reason to Choose Data Science for Python:

  • Simplicity and Readability: Python's syntax is easy to understand and read, making it beginner-friendly and accessible for those new to programming or data science. This simplicity allows data scientists to focus more on solving problems and analyzing data rather than dealing with complex syntax.
  • Rich Ecosystem of Libraries: Python has a vast a network of libraries created expressly for data science and tools for machine learning, including TensorFlow, Pandas, Scikit-learn, Matplotlib, and NumPy. These libraries provide powerful tools and functionalities for data manipulation, analysis, visualization, and building machine learning models, reducing development time and effort.
  • Versatility and Integration: Python is a versatile language. It has many different applications. It seamlessly integrates with other technologies, databases, and tools, allowing data scientists to combine Python with existing systems and work with various data sources.
  • Strong Community and Support: Python has a large and active community of data scientists, developers, and researchers. This vibrant community contributes to the development and improvement of data science libraries, provides support through forums, online communities, and extensive documentation, and shares a wealth of resources and best practices.
  • Adoption in Industry: Python has gained significant adoption in the data science industry. Many organizations, including top tech companies and startups, use Python extensively for data analysis, machine learning, and building data-driven applications. Learning Python for data science opens up abundant career opportunities and ensures compatibility with industry standards.
  • Educational Resources and Learning Curve: Python has an abundance of learning resources, tutorials, and courses dedicated to data science. Its popularity as a language for teaching and learning data science means there are numerous educational materials available, making it easier for beginners to get started and progress in their data science journey.

Trending Opinions on Python Data Science:

  • High need: The need for data scientists is rising with Python skills as organizations increasingly recognize the importance of leveraging data for insights and decision-making. Python's versatility, ease of use, and extensive library ecosystem make it a preferred choice for data science projects.
  • Widely Adopted: Python has gained widespread adoption in the data science community. It is the go-to language for many data scientists and researchers due to its extensive range of specialized libraries, such as Pandas, NumPy, and Scikit-learn, that facilitate data manipulation, analysis, and machine learning tasks.
  • Accessibility and Learning Curve: Python's intuitive syntax and readability make it accessible for beginners, enabling individuals with diverse backgrounds to enter the field of data science. The abundance of learning resources, tutorials, and online courses further contribute to its popularity and ease of learning.
  • Integration with Big Data and AI Technologies: Python seamlessly integrates with big data processing frameworks like Hadoop and Spark, enabling efficient data handling and analysis at scale. Additionally, Python's compatibility with artificial intelligence (AI) frameworks like TensorFlow and PyTorch enhances its utility in advanced data science applications.
  • Community and Support: Python has a vibrant and supportive community of data scientists, researchers, and developers. This community actively contributes to the development of data science libraries, shares knowledge and best practices, and provides support through forums and online communities.
  • Career Opportunities: Data scientists with Python skills are in high demand, with ample career opportunities available across a variety of sectors, including technology, finance, healthcare, e-commerce, and more. Python's prevalence in job postings and its inclusion as a requirement in data science job descriptions highlight its significance in the current job market.

Additional Business Trends Using Python and Data Science:

In addition to the trending perception of Data Science with Python, there are several industry trends that highlight the growing importance and impact of Python in the field.

  • AI and Machine Learning: Python has emerged as a dominant language for Data Science & Ai and machine learning applications. Its flexibility, along with powerful libraries like TensorFlow, PyTorch, and Keras, has made it the go-to language for building and deploying machine learning models.
  • Automation and Data Pipelines: Python's simplicity and wide range of libraries make it ideal for automating data-related tasks and building efficient data pipelines. Python frameworks like Airflow and Luigi enable the creation and management of complex data workflows.
  • Natural Language Processing (NLP): Python has become the de facto language for NLP applications. Libraries such as NLTK, SpaCy, and Gensim provide robust tools for text processing, sentiment analysis, language modeling, and other NLP tasks.
  • Data Visualization: Python's data visualization libraries, including Matplotlib, Seaborn, and Plotly, offer rich and interactive visualizations, allowing data scientists to communicate insights effectively and create compelling data-driven stories.
  • Big Data and Distributed Computing: Python is increasingly being used in conjunction with big data processing frameworks like Apache Spark, allowing data scientists to analyze large-scale datasets and perform distributed computing tasks efficiently.
  • Collaborative Development: Python's popularity and ease of use promote collaborative development practices. Data scientists can leverage Python's package ecosystem to share code, build reusable modules, and collaborate on open-source projects, fostering innovation and knowledge exchange.
  • Data Science Platforms: Many data science platforms and tools, such as Anaconda, Jupyter Notebooks, and Google Colab, provide Python-based environments that facilitate exploratory analysis, model development, and collaboration among data scientists.
  • Interdisciplinary Applications: Python's versatility and accessibility have led to its adoption beyond traditional data science domains. It is being utilized in interdisciplinary applications, including bioinformatics, social sciences, finance, and IoT, demonstrating its broad applicability.
  • Ethics and Responsible AI: With the increased focus on ethics in AI and responsible data science, Python frameworks like AI Fairness 360 and responsible AI libraries provide tools and resources to address biases, fairness, and ethical considerations in machine learning models.

Implementing Industry Tools in Python for Data Science:

Data Science with Python leverages a variety of industry tools to enhance data analysis, model development, and deployment.

  • Jupyter Notebooks: Jupyter Notebooks provide an interactive and collaborative environment for data exploration, code development, and documentation. It allows data scientists to combine code, visualizations, and explanatory text in a single, shareable document.
  • Pandas: Pandas is a robust Python data analysis and manipulation toolkit. It provides high-performance data structures and data analysis tools, making it efficient for cleaning, transforming, and analyzing structured data.
  • Scikit-learn: Scikit-learn is a popular Python package for machine learning. It offers a comprehensive range of machine-learning algorithms for classification, regression, clustering, and model evaluation, along with utilities for preprocessing and feature selection.
  • TensorFlow and Keras: TensorFlow is an open-source deep learning framework, while Keras is a user-friendly neural network library. Together, they enable the development and training of complex deep-learning models for jobs including time series analysis, natural language processing, and picture identification.
  • Matplotlib and Seaborn: Matplotlib and Seaborn are popular data visualization libraries in Python. They provide a wide range of customizable plots, charts, and graphs, allowing data scientists to effectively communicate insights and patterns in their data.
  • NumPy:NumPy is an essential Python package for scientific computing. It provides efficient data structures and numerical operations, enabling fast array processing and mathematical computations necessary for data science tasks.
  • Spark: Apache Spark is a distributed computing framework that can be seamlessly integrated with Python. It enables scalable data processing, big data analysis, and distributed machine learning, making it valuable for handling large-scale datasets and complex computations.
  • SQL and Database Integration: Python offers robust support for interacting with databases through libraries such as SQLAlchemy and panda sql. This allows data scientists to connect to various database systems, execute SQL queries, and perform data extraction and manipulation.
  • Flask and Django: Flask and Django are popular web development frameworks in Python. They enable the creation of web-based data applications, APIs, and dashboards to showcase data analysis results and make data-driven insights accessible to users.
  • Docker and Kubernetes: Docker and Kubernetes are containerization and orchestration tools that are often used for deploying data science models and applications. They provide scalability, reproducibility, and efficient deployment of Python-based data science solutions.
  • Implementing these industry tools in Data Science with Python empowers data scientists to effectively analyze, model, visualize, and deploy data-driven solutions, enhancing their productivity and the impact of their work.

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Key Features

ACTE Bangalore offers Data Science with Python Training in more than 27+ branches with expert trainers. Here are the key features,
  • 40 Hours Course Duration
  • 100% Job Oriented Training
  • Industry Expert Faculties
  • Free Demo Class Available
  • Completed 500+ Batches
  • Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.


Syllabus of Data Science with Python Training in Bangalore
Module 1 : Introduction to Data Science and ML using Python
  • 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
Module 2 : Data Handling, Sequences and File Operations
  • 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
Module 3 : Deep Dive – Functions, OOPs, Modules, Errors, and Exceptions
  • 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
Module 4 : Introduction to NumPy, Pandas, and Matplotlib
  • 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
Module 5: Exceptions Handling
  • Errors
  • Exception handling with try
  • handling Multiple Exceptions
  • Writing your own Exception
Module 6 : 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
Module 7 : Introduction to Machine Learning with Python
  • What is Machine Learning?
  • Machine Learning Use-Cases
  • Machine Learning Process Flow
  • Machine Learning Categories
  • Linear regression
  • Gradient descent
Module 8: Supervised Learning - I
  • 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?
Module 9: Dimensionality Reduction
  • Introduction to Dimensionality
  • Why Dimensionality Reduction
  • PCA
  • Factor Analysis
  • Scaling dimensional model
  • LDA
Module 10 : Association Rules Mining and Recommendation Systems
  • What are Association Rules?
  • Association Rule Parameters
  • Calculating Association Rule Parameters
  • Recommendation Engines
  • How do Recommendation Engines work?
  • Collaborative Filtering
  • Content-Based Filtering
Module 11: Reinforcement Learning
  • 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
Module 12 : Time Series Analysis
  • What is Time Series Analysis?
  • Importance of TSA
  • Components of TSA
  • White Noise
  • AR model
  • MA model
  • ARMA model
  • ARIMA model
  • Stationarity
  • ACF & PACF
Module 13: Model Selection and Boosting
  • What is Model Selection?
  • Need for Model Selection
  • Cross Validation
  • What is Boosting?
  • How do Boosting Algorithms work?
  • Types of Boosting Algorithms
  • Adaptive Boosting
Module 14: Statistical Foundations
  • 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
Module 15: Database Integration with Python
  • Basics of database management
  • Python MySql
  • 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
Module 16: Data Connection and Visualization in Tableau
  • 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
Module 17: Advanced Visualizations
  • Trend lines
  • Reference lines
  • Forecasting
  • Clustering
  • Geographic Maps
  • Using charts effectively
  • Dashboards
  • Story Points
  • Visual best practices
  • Publish to Tableau Online
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Need customized curriculum?

Hands-on Real Time Data Science with Python Projects

Project 1
E-commerce Price Optimization

Create a price optimization system for e-commerce products to maximize revenue and competitiveness.

Project 2
Agricultural Yield Prediction

Predict crop yields based on historical agricultural data, weather information, and soil properties.

Get Our Python Data Science Job Opportunities

ACTE Bangalore provides comprehensive Data Science with Python data analyst course training that covers methods, applicability, and products related to data science.

  • We have partnered with over 600 organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM, etc. to provide placement opportunities for their Data Science and Python course students
  • The Active Recruitment provides dedicated support to job seekers, helping them find their rightful place.
  • Upon completion of the training, eligible students receive 100% Python Data Science Job support, including resume preparation and face-to-face interview guidance.
  • Data Science with Python tutors helps students build industry-relevant projects, and focuses on their knowledge and skills in data analysis using Python.
  • ACTE operates as a one-stop shop, providing exceptional support to top job seekers and recruiters.
  • Regular mock interviews and group discussions are held to identify knowledge gaps and enhance candidates’ readiness for real-world job interviews.
  • In addition to data science with Python, ACTE also offers the Python Data Analyst course, giving students the skills to analyze, visualize and interpret data using Python

Gain Our Data Science with Python certification

We offer a widely recognized Data Science with Python certification that is accredited by giant multinational companies worldwide. This certification enhances the value of your resume and increases your chances of securing a position at major MNCs. By utilizing NumPy, pandas, and sci-kit-learn, our comprehensive training equips both freshers and corporate trainees with the skills to analyze data using multi-dimensional arrays and machine learning techniques. Upon completion of the Data Science with Python online training and practical-based activities, you will receive a Data Science with Python certification from ACTE.
Obtaining a Data Science with Python Training certification can greatly benefit your career by showcasing your proficiency in data science techniques, Python programming, and machine learning. It demonstrates your commitment to professional development and enhances your credibility among employers.
  • Prerequisites for enrolling in the Data Science with Python Training certification may vary depending on the specific program.
  • However, having a basic understanding of programming concepts and familiarity with Python can be advantageous for a smoother learning experience.
Yes, Earning a Data Science with Python certification can enhance your qualifications and make you a more competitive candidate in the job market. Several factors influence your employability, including your overall skills, experience, and the job market conditions in your region.
  • The duration to complete the Data Science with Python Training certification program can vary based on the program structure and learning pace.
  • It typically ranges from a few weeks for intensive bootcamp-style programs to several months for more comprehensive training that covers advanced topics.
    Different types of certifications available in Data Science with Python Training include:
  • Foundation Certification
  • Advanced Certification
  • Specialization Certification
  • Professional Certification

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

Get Certified

a physical version of your officially branded and security-marked Certificate.

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Python Trainer: Industry Specialists with Extensive Experience

  • Our Data Science with Python Training is conducted by industry specialists, with an average of more than 9+ years of experience, serving as Python trainer.
  • Both on-site and online training options are available to cater to individual preferences and requirements.
  • Trainers, who are working professionals in the Data Science with Python domain, utilize real-world projects to deliver practical training sessions.
  • Participants receive personalized one-on-one instruction from industry experts who are enthusiastic about sharing their knowledge and experiences.
  • Our Placement Support team excels in helping learners find suitable job opportunities in the IT industry.
  • Learners receive comprehensive Interview Preparation and Soft Skills training from mentors who provide valuable insights into interview scenarios and questions.
  • Our Data Science with Python Training in Bangalore has been recognized with prestigious awards from renowned IT companies, establishing our reputation as a top-notch training provide.

Data Science with Python Course Reviews

Our ACTE Bangalore Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.


Data Analyst

If you're looking for an institute which teaches everything from the basics to the core, this ACTE is the right place for you. Highly efficient staff and management team. Great for Data Science with Python, Data analytics and Big data courses. And I am thankful to the team for their support and guidance. Highly recommended.

Sherin Roselin


I had completed my Data Science with Python course at Bangalore. ACTE is the best place to improve your skills and to move forward in your career. The trainers and faculty here were very friendly and comfortable. My trainer had explained the concept as well as the subject in clear way. Topics are not skipped and trainer ensures that you understand the topic. Thanks to my trainer and ACTE for this wonderful opportunity!


Software Engineer

Ive completed my Data Science with Python course from ACTE where Ive experienced a good faculty and teaching way in a knowledgable manner. I would suggest each and everyone who are aspiring for data scientists or data analytics to join in ACTE and gain good knowledge at the centre of city Velachery, Chennai.


One of the best place to learn Data Science with Python Course Training in Omr. Friendly Environment.Great course for the people who are looking for a better career.This course covers the Data Science with Python knowledge.



ACTE is the best place to kick start Data Science with Python and other Data Science courses in Anna Nagar. Their guidence is good and at the same time providing better lab practice.Which helps you make informed predictions and assure you to move forward,Honestly, I would definitely recommend this place for Data Science with Python, Data Analytics using R,Big Data,Machine Learning,Business Analytics..

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Data Science with Python Course FAQs

Looking for better Discount Price?

Call now: +91 93833 99991 and know the exciting offers available for you!
  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
ACTE gives Certificate for completing a course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Data Science with Python training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Data Science with Python Course At ACTE?

  • Data Science with Python Course in ACTE is designed & conducted by Data Science with Python experts with 10+ years of experience in the Data Science with Python domain
  • Only institution in India with the right blend of theory & practical sessions
  • In-depth Course coverage for 60+ Hours
  • More than 50,000+ students trust ACTE
  • Affordable fees keeping students and IT working professionals in mind
  • Course timings designed to suit working professionals and students
  • Interview tips and training
  • Resume building support
  • Real-time projects and case studies
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), Singapore.
We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Data Science with Python batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Data Science with Python. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
You can contact our support number at +91 93800 99996 / Directly can do by's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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