Top Data Science Course in Pune for Job Oriented Learning
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Data Science Course in Pune

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  • Beginner and Advanced Level Classes
  • Top MNC Interview Questions Coverage and More
  • Trendy Projects and Advanced Research Resources are Available
  • Benefited 11,402+ Students With Training and Served 320+ Clients
  • Delivered by a Certified Data Science Trainer With Over 9+ Years of Experience
  • Next Data Science Batch to Begin This Week – Enroll Your Name Now!

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Price

INR18000

INR 14000

Price

INR 22000

INR 18000

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+91-7669 100 251

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Upcoming Batches

15-July-2024
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

10-July-2024
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

13-July-2024
Sat,Sun

Weekend Regular

(10:00 AM - 01:30 PM)

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

13-July-2024
Sat,Sun

Weekend Fasttrack

(09:00 AM - 02:00 PM)

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

Hear it from our Graduate

Have Cracked Their Dream Job in Top MNC Companies

Enhance Your Profession With Our Data Science Training Program

  • Our comprehensive Data Science Training curriculum covers every field facet, from basic concepts to cutting-edge methods, equipping students with the abilities needed to thrive in this fast-paced industry.
  • Through practical exercises, real-world projects, and case studies, students gain crucial practical experience that prepares them to handle Data Science challenges in real-world scenarios.
  • Our dedicated job support team offers targeted interview preparation workshops to ensure students are ready to showcase their abilities and explore profitable career opportunities in data science.
  • Gain an edge in data science by learning advanced techniques like big data analytics, deep learning, and machine learning. Master these methods to stay ahead of industry trends.
  • We allow students to specialize in their areas of interest by teaching a broad range of Data Science disciplines, including statistical analysis, predictive modeling, and data manipulation.
  • Our Data Science Training curriculum is continually refreshed to encompass the latest industry advancements and trends. Innovations and trends are created with industry experts to guarantee that students acquire marketable skills.
  • After the course, students can choose from a wide selection of data science career tracks, such as business analyst, machine learning engineer, data scientist, and more, which provides a wealth of exciting options in the field.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

Course Objectives

  • Enhanced job prospects in data analysis and machine learning.
  • Higher earning potential due to specialized skills.
  • Practical experience with real data sets.
  • Competitive edge through staying updated with the latest tools.
    • Statistics
    • Machine learning
    • Data visualization
    • Big data technologies
    • Data manipulation
    • Data mining
    • Programming languages (Python, R)
    • Develop proficiency in collecting and cleaning large datasets.
    • Develop your ability to analyze facts to draw insightful conclusions.
    • Learn techniques for evaluating the quality and reliability of data.
    • Enhance communication abilities to convey analytical findings effectively.

    There is a growing need for data scientists and analysts in various industries, so taking a data science course will be very helpful for future job prospects. Because data scientists can glean valuable insights from data and apply them to make better decisions, they are in high demand.

  • Data Scientist
  • Data Analyst
  • Machine Learning Engineer
  • Business Intelligence Analyst
  • Data Engineer
  • Data Architect
  • Statistician

    Proficiency in mathematics and statistics, backed by a solid foundation, is essential. With programming languages like Python or R, familiarity with databases and data processing tools, and the capacity for critical thought are frequently prerequisites for enrollment in data science courses.

  • Python
  • R
  • SQL
  • Matplotlib
  • Pandas
  • Scikit-learn

Is Data Science easy to understand?

Data science can be straightforward and easy to understand with the right approach. While it may have complexities, breaking down concepts into manageable parts and practicing regularly can make it accessible. With dedication and patience, individuals can grasp the fundamental principles of data science and excel in the field.

How will completing the Data Science course advance my career?

After completing the Data Science course, students will advance in their professions by assuming more responsibility, concentrating on particular data science domains, pursuing further degrees or certifications, and participating in innovative data-driven projects.

What Skills Are Acquired Through Data Science Courses?

  • Programming skills (Python, R)
  • Statistical knowledge
  • Machine learning proficiency
  • Data visualization expertise
  • Data manipulation skills (using tools like Pandas)
  • Problem-solving abilities

Is training in data science really necessary?

Yes, data science training is in great demand as firms rely more on data for decision-making. This need is driven by the requirement for experienced people who can extract meaningful insights from massive datasets using data analysis, machine learning, and statistical modeling. Pursuing Data Science training may lead to lucrative employment prospects in various fields.

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Overview Of Data Science

Data science is an interdisciplinary field that draws conclusions and information from data using computational techniques, machine learning, and statistical analysis. Large datasets are collected, cleaned, and processed to reveal patterns, trends, and correlations. Programming languages like R and Python are used by data scientists, together with specific tools and algorithms, to analyze data and offer insightful analysis in the discipline of data science. Making informed business decisions, streamlining processes, and creating predictive models all benefit from these insights. A data science course covers subjects like statistical analysis, machine learning, and data visualization and gives prospective professionals the tools they need to succeed in this field. Applications of data science are found in banking, healthcare, marketing, and technology, among other fields. These applications foster innovation and the success of organizations.Enrolling in a reputable data science course in Pune can provide individuals with the expertise needed to thrive in this rapidly evolving field.

Additional Info

Benefits of Data Science Integration

  • Informed Decision-Making: Organizations can improve strategy planning and resource allocation by utilizing data-driven insights to enhance decision-making through the integration of data science.
  • Predictive Analytics: By leveraging Data Science techniques, organizations can predict future trends, customer behaviors, and market demands, allowing them to respond proactively to changing conditions.
  • Improved Efficiency and Productivity: Data Science integration automates manual processes, streamlines workflows, and identifies inefficiencies, improving operational efficiency and productivity.
  • Enhanced Customer Experience: Through Data Science, organizations can analyze customer data to personalize offerings, improve customer service, and enhance overall satisfaction.
  • Cost Reduction: Data Science integration helps optimize resource utilization, minimize waste, and identify cost-saving opportunities, reducing operational expenses.
  • Competitive Advantage: Effective Data Science integration gives businesses a competitive edge by helping them keep ahead of market trends, better understand their customers' needs, and innovate more quickly.
  • Risk Mitigation: Data Science enables organizations to identify and mitigate risks through predictive modeling, fraud detection, and anomaly detection, reducing potential losses and liabilities.
  • New Revenue Streams: Enterprises can generate new revenue streams through data analysis and opportunity identification, which can result in the development of creative goods, services, and business models.

Tools used for data science training

  • Jupyter Notebook : Jupyter Notebook is a free and open-source web tool that lets you create and share documents with live code, math, images, and narrative prose.
  • Python: Given its many libraries, such as NumPy, Pandas, and Scikit-Learn, Python is a versatile programming language widely used in scientific computing, machine learning, and data analysis.
  • R: R is an environment and programming language designed primarily for statistical computation and graphics. It is widely employed in data visualization and analysis.
  • SQL: SQL is a domain-specific language that facilitates fast data retrieval and updating. It is used to manage and query relational databases. SQL proficiency is required to access structured data, run complicated queries, and guarantee data integrity, making it a critical ability for data professionals.
  • Git: Git is a version control system used to monitor code changes, collaborate with other users, and effectively manage projects; it is frequently combined with platforms such as GitHub or GitLab.
  • TensorFlow: Deep learning models are frequently created and trained using TensorFlow, an open-source machine learning framework created by Google. It is utilized for tasks including image identification and natural language processing.
  • PyTorch: PyTorch is another prominent open-source machine learning framework created by Facebook's AI Research group. It is noted for its flexibility and simplicity of use for developing neural networks.
  • Tableau: Tableau is a robust data visualization application that allows users to create interactive and shared dashboards, allowing for easy investigation and discussion of data insights.
  • Apache Spark: Apache Spark is a fast and versatile distributed computing system for large-scale data processing. It includes modules for data analysis, machine learning, graph processing, and streaming analytics.
  • Docker: Docker is a platform for creating, delivering, and executing programs in containers. It enables the simple deployment and scalability of data science projects across several settings.

Skills Acquired from Our Data Science Training

  • Machine Learning: Machine learning is the process by which computers may learn from data and form opinions or predictions. It encompasses classification (categorizing data points), regression (predicting numerical values), and clustering.
  • Statistical Analysis: Statistical analysis entails applying statistical tools and procedures to investigate, analyze, and draw conclusions from data. This comprises measurements of central tendency, dispersion, hypothesis testing, and regression analysis better to understand the data's underlying patterns and relationships.
  • Programming: Understanding programming languages like Python, R, and SQL is required for data manipulation, analysis, and modeling. This includes creating code to clean, transform, and analyze data, building machine learning models, and accessing databases.
  • Data wrangling: Data wrangling, also known as data munging, is the act of cleaning, preparing, and changing raw data into a format suitable for analysis. It involves duties such as managing missing values, deleting duplicates, and altering data structures.
  • Feature engineering: To increase the accuracy and performance of machine learning models, feature engineering is extracting new features or variables from the available data. This comprises identifying important characteristics, merging or manipulating variables, and generating new data representations.
  • Big Data Technologies: Big data technologies include Hadoop, Spark, and Kafka, which are used to manage and analyze enormous amounts of data efficiently. These solutions offer distributed computing frameworks for storing, processing, and analyzing data at scale.
  • Domain Knowledge: Domain knowledge refers to a grasp of certain businesses or areas, such as finance, healthcare, and marketing. It enables data analysts and scientists to contextualize their analyses, discover significant factors, and deliver actionable insights customized to the industry's unique requirements.
  • Statistical Analysis: Statistical analysis entails applying statistical tools and procedures to investigate, analyze, and draw conclusions from data. This comprises measurements of central tendency, dispersion, hypothesis testing, and regression analysis better to understand the data's underlying patterns and relationships.
  • Programming: Understanding programming languages like Python, R, and SQL is required for data manipulation, analysis, and modeling. This includes creating code to clean, transform, and analyze data, building machine learning models, and accessing databases.
  • Data wrangling: Data wrangling, also known as data munging, is the act of cleaning, preparing, and changing raw data into a format suitable for analysis. It involves duties such as managing missing values, deleting duplicates, and altering data structures.
  • Big Data Technologies: Big data technologies include Hadoop, Spark, and Kafka, which are used to manage and analyze enormous amounts of data efficiently. These solutions offer distributed computing frameworks for storing, processing, and analyzing data at scale.
  • Domain Knowledge: Domain knowledge refers to a grasp of certain businesses or areas, such as finance, healthcare, and marketing. It enables data analysts and scientists to contextualize their analyses, discover significant factors, and deliver actionable insights customized to the industry's unique requirements.
  • Communication: Effective communication skills are required for data professionals to transmit complicated technical concepts and insights to non-technical stakeholders. This involves drafting reports, presenting results, and presenting them clearly and intelligibly.

Roles and Responsibilities for Data Science Professionals

  • Data Scientist: Analyzes complex data sets using statistical techniques and machine learning algorithms, collaborating with cross-functional teams to solve business problems and drive strategic decisions.
  • Machine Learning Engineer: Designs, implements, and optimizes machine learning models, working closely with data scientists and software engineers to deploy scalable solutions that meet business objectives.
  • Data Analyst: Collects, cleans, and interprets data to uncover insights and trends, presenting findings through reports and visualizations to support department decision-making processes.
  • Business Intelligence Analyst: Develops interactive dashboards and reports using BI tools like Tableau or Power BI, working together with stakeholders to comprehend business needs and deliver helpful information.
  • Data Engineer: Builds and maintains data pipelines to ensure efficient data ingestion, processing, and storage, leveraging technologies like Apache Spark and AWS services to support analytics and machine learning workflows.
  • Research Scientist: This person conducts experiments, analyzes data, and develops prototypes for novel algorithms and models, contributing to cutting-edge research in areas like natural language processing or computer vision.
  • Big Data Engineer: This person designs and implements scalable infrastructure for processing and analyzing large volumes of data, optimizing the performance and reliability of distributed systems to support data-driven decision-making.
  • Data Architect: Designs data models and schemas, defines data integration strategies, and ensures data quality and governance standards are maintained, aligning architecture with business objectives and scalability requirements.
  • Quantitative Analyst: This person utilizes mathematical and statistical techniques to analyze financial data, developing models for risk assessment, portfolio optimization, and algorithmic trading strategies, contributing to informed investment decisions.
  • AI Ethics Specialist: This position guides the development and deployment of AI systems, assessing potential ethical implications and implementing measures to mitigate biases, ensure fairness, and uphold ethical standards throughout the AI lifecycle.
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Key Features

ACTE Pune offers Data Science Training in more than 27+ branches with expert trainers. Here are the key features,
  • Get Qualified from Professional Expert
  • 100% Job placements
  • Industry Expert Faculties
  • Learn Data science from scratch
  • 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.
 

Curriculum

Synopsis of Data Science Course in Pune
Module 1: Data Science Basics
  • What is Data Science
  • Significance of Data Science in today’s world
  • R Programming basics
  • Data Science Methodology
  • Data Acquisition and Cleaning
  • Exploratory Data Analysis (EDA)
Module 2: Python Fundamentals
  • Python Introduction
  • Indentations in Python
  • Python data types and operators
  • Python Functions
Module 3: Data Structures and Data Manipulation
  • Data Structures Overview
  • Identifying the Data Structures
  • Allocating values to the Data Structures
  • Data Manipulation Significance
  • Using Dplyr for various data manipulations
Module 4: Data visualization
  • Intro to Data Visualization
  • Graph Types, Graphics Grammar
  • Ggplot2 Package
  • Multivariate Analysis: geom_boxplot
  • Univariate Analysis: histogram, barplot, distribution, density
  • Bar Plots with geom_bar(), Themes with theme()
Module 5: Statistics
  • Statistics Importance
  • Stats Classification, Terminology
  • Data Types, Probability, Central Tendency
  • Covariance, Correlation, Distributions
  • Data Sampling, Confidence Levels
  • Hypothesis Test and Parametric testing
Module 6: Introduction to Machine Learning
  • Machine Learning Fundamentals
  • Supervised Learning, Classification
  • Linear Regression, Mathematical Concepts
  • Classification Algorithms, Ensemble Learning
Module 7: Logistic Regression
  • Logistic Regression Introduction
  • Regression Methods: Logistic, Linear, Poisson
  • Bivariate Logistic Regression & Math
  • Multivariate Logistic Regression & Modeling
  • True/False Positive Rates
  • Real-time Logistic Regression Applications
Module 8: Random Forest and Decision Trees
  • Classification Techniques
  • Random Forest Implementation in R
  • Classification vs. Regression Trees Differences
  • Naive Bayes, SVM
  • Entropy, Gini Index, Information Gain
Module 9: Unsupervised learning
  • Clustering Methods
  • Unsupervised Learning
  • K-means
  • Historical Clustering in R
  • PCA Implementation in R
Module 10: Natural Language Processing
  • NLP and Text Mining Basics
  • Text Mining Significance and Use-cases
  • NLP with NLTK
  • Text Mining
Module 11: Mathematics for Data Science
  • Numpy Basics
  • Numpy Mathematical Functions
  • Probability Basics and Notation
  • Correlation and Regression
  • Joint Probabilities
  • Bayes Theorem
  • Conditional Probability, sum rule, and product rule
Module 12: Python Integration with Spark
  • Pyspark basics
  • Uses and Need of pyspark
  • Pyspark installation
  • Advantages of pyspark over MapReduce
  • Pyspark applications
Module 13: Tableau
  • Data Visualisation Basics
  • Data Visualisation Applications
  • Tableau Installation and Interface
  • Tableau Data Types, Data Preparation
  • Tableau Architecture
  • Getting Started with Tableau
  • Creating sets, Metadata and Data Blending
  • Arranging visual and data analytics
  • Mapping, Expressions, and Calculations
  • Parameters and Tableau prep
  • Stories, Dashboards, and Filters
  • Graphs, charts
  • Integrating Tableau with Hadoop and R
Module 14: MongoDB
  • MongoDB and NoSQL Basics
  • MongoDB Installation
  • Significance of NoSQL
  • CRUD Operations
  • Data Modeling and Management
  • Data Indexing and Administration
  • Data Aggregation Schema
  • MongoDB Security
  • Collaborating with Unstructured Data
Module 15: SAS
  • SAS Basics
  • SAS Enterprise Guide
  • SAS functions and Operators
  • SAS Data Sets compilation and creation
  • SAS Procedures
  • SAS Graphs
  • SAS Macros
  • PROC SQL
  • Advance SAS
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Need customized curriculum?

Get Hands-on Knowledge with Industrial Live Data Science Projects

Project 1
Exploratory Data Analysis (EDA)

Perform EDA to analyze sentiment distribution, visualize review frequencies, and identify keywords for each sentiment.

Project 2
Continuous Monitoring and Improvement

Continuously gather user feedback to refine the model and incorporate new data for improved analysis.

Boost Your Potential With Our Data Science Placement Program

  • Personalized training courses prepare you for Data Science interviews by addressing typical scenarios and industry-specific questions.
  • Access internship opportunities through our Data Science placement and training program, supervised by industry professionals, providing hands-on project experience.
  • Receive tailored career counseling sessions to explore career routes and strategies for success in Data Science.
  • Gain access to placement opportunities with top organizations like Google, Microsoft, Amazon, Facebook, etc., ensuring long-term professional success.
  • Avail resume writing and presentation services to enhance visibility and job prospects in Data Science placement program.
  • Collaborate with diverse Data Science groups for real-world applications, fostering deeper learning and skill refinement.
  • Participate in data science-focused networking events and job fairs to connect with potential employers and showcase expertise.
  • Exclusive networking events and job fairs for data science professionals offer prime opportunities to network and impress potential employers.

Acquire Advanced Data Science Certification

Our Data Science Certification is well-established, with prominent companies highlighting its applicability to professionals across all expertise levels. This accreditation raises your professional reputation and improves your chances of partnering with significant organizations because it is widely recognized in the industry. Ensuring a comprehensive understanding of Data Science principles and procedures through hands-on assignments and participation in immersive training sessions are prerequisites for this certification.

  • Data Science Professional Certificate
  • Machine Learning Engineer Certification
  • Big Data Analytics Certification
  • Data Visualization Certification
  • Data Engineering Certification

Yes, our data science certification significantly increases job prospects and guarantees employment readiness. It validates expertise, boosts credibility, and enhances visibility to potential employers. Certification assures access to numerous rewarding career opportunities in the thriving data-driven landscape.

Certainly, acquiring a Data Science certification has the potential to increase salary over time. It validates expertise, demonstrates dedication to professional growth, and strengthens one's position in salary discussions.

  • Improved job opportunities in diverse industries.
  • Valuable skills in data analysis and machine learning.
  • Practical experience and networking opportunities.

To prepare for the Data Science certification test, it is recommended that you use extensive study resources, practice with datasets and algorithms, seek advice from experienced experts, and take mock exams to check your preparation.

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.

Get Certified

Building a Career With Our Data Science Trainers

  • Please take advantage of our experienced data science trainers' extensive industry knowledge and valuable suggestions to enhance the training curriculum.
  • Our trainers deliver a comprehensive curriculum covering essential concepts, procedures, and resources vital for success in the data science job field.
  • Benefit from guided practical projects, case studies, and real-world applications from our knowledgeable data science trainers.
  • Receive personalized career guidance and support from our data science trainers as you explore job opportunities, market trends, and professional growth paths.
  • Access ongoing guidance and resources from our data science instructors throughout your career journey to continually enhance your knowledge and skills.
  • Join our expert trainers and peers to expand your professional network, collaborate on projects, and discover employment prospects in the industry.
  • Receive personalized guidance from our data science experts to achieve your career goals. Access tailored insights and support to thrive in data science.

Data Science Course FAQs

Looking for better Discount Price?

Call now: +9193833 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 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 ScienceCourse At ACTE?

  • Data Science Course in ACTE is designed & conducted by Data Science experts with 10+ years of experience in the Data Science 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 batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Data Science. 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 93833 99991 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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      Job Opportunities in Data Science

      More Than 35% Of Developers Prefer Data Science. Data Science Is The Most Popular And In-Demand Programming Language In The Tech World.

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