Data Science Training in Marathahalli

Data science training in Marathahalli, Elegant IT Services conducts tutorials. The main subjects that will be taught are visualization, machine learning, and big data analysis, which are also part of our course. For you to succeed in your studies concerning data science, we will provide highly qualified teachers as well as practical’s that have to be done under their guidance. Whether one is a novice or looking forward to sharpening their skills, this is the right place due to the good supportive environment created in this area.

Students Enrolled
25,213

Reviews 566+

Duration
40 Hours / 2 Month

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Data Science Training in marathahalli Course Content

  •  What is Data Science?
    – Understanding the sector and its importance
  •  History of Data Science
    – Evolution and milestones in Data Science
  • Data Science Process and Lifecycle
    – Steps concerned from statistics series to deployment
  • Data Science Roles
    – Data Scientist: Focus on analysis and modelling
    – Data Engineer: Handle facts infrastructure and pipelines
    -Data Analyst: Interpret and visualize statistics
  • Data Science Applications
    – How one-of-a-kind industries make use of facts technology (e.g., healthcare, finance, marketing)

  • Python Programming
    – Basics: Syntax, variables, and records kinds
    – Control Structures: Loops and conditional statements
    – Functions and Modules: Writing reusable code
    – Data Structures: Lists, tuples, dictionaries, units
    – Libraries: Using NumPy, Pandas for facts manipulation, matplotlib, and Seaborn for visualization
  • R Programming
    – Basics: Syntax, variables, information types
    – dplyr: Data manipulation
    – ggplot2: Data visualization
    -R for Statistical Analysis
  • Data Manipulation
    – Importing and exporting data
    – Cleaning information: Handling missing values and outliers
    – Data transformation: Sorting, filtering, aggregation
    – Merging and joining datasets
  • Data Visualization
    – Basic plots: Line, bar, histogram, pie
    – Advanced visualizations: Boxplot, heatmap, pair plot
    – Interactive visualizations with Plotly
    – Dashboard advent with Tableau or Power BI
  •  Descriptive Statistics
    – Central tendency: Mean, median, mode
    – Dispersion: Range, variance, popular deviation
    – Skewness and kurtosis
  • Inferential Statistics
    – Probability theory and distributions
    – Sampling and sampling distributions
    – Hypothesis testing: t-tests, chi-square check, ANOVA
    – Confidence durations and p-values
    – Correlation and causation
  • Supervised Learning
    – Regression analysis: Linear, logistic
    – Classification algorithms: Decision timber, k-nearest acquaintances, aid vector machines, Naive Bayes
    – Model evaluation: Confusion matrix, ROC curve, precision, recall, F1 score
  • Unsupervised Learning
    – Clustering: K-means, agglomerative clustering, DBSCAN
    – Dimensionality discount: PCA, t-SNE
  • Model Optimization
    – Cross-validation strategies
    – Hyperparameter tuning: Grid search, random seek
    – Ensemble techniques: Bagging, boosting, random wooded area, gradient boosting machines (GBM), XGBoost

  •  Deep Learning
    – Introduction to neural networks
    – Frameworks: TensorFlow, Kera’s, PyTorch
    – Convolutional Neural Networks (CNNs) for photograph processing
    – Recurrent Neural Networks (RNNs) for time series and NLP
    – Transfer gaining knowledge of and pre-trained models
  • Deep Learning Techniques
    – Text preprocessing: Tokenization, lemmatization, forestall word removal
    – Sentiment analysis, subject matter modelling
    – Word embeddings: Word2Vec, Glove
    – Sequence models: LSTM, GRU
  • Time Series Analysis
    – Decomposition of time collection
    – ARIMA and exponential smoothing
    – Forecasting and anomaly detection

  •  Hadoop Ecosystem
    – Introduction to Hadoop and HDFS
    – The MapReduce programming version
    – Data processing with Apache Pig and Hive
  • Apache Spark
    – Spark Core and RDDs
    – Spark SQL and Data Frames
    – Spark Streaming
    – Machine gaining knowledge of with MLlib
  •  NoSQL Databases
    – Introduction to NoSQL
    – Databases like MongoDB and Cassandra
    – Key-cost stores and document databases

  • The ETL Process
    – Data ingestion: Batch and actual-time
    – Data cleaning and transformation
    – Data loading strategies
  • Data Pipeline Design
    – Pipeline orchestration with the use of Apache Airflow
    – Data integration gear: Talend, Informatica
  •  Cloud Data Engineering
    – AWS Data Services: S3, Redshift, Glue
    – Google Cloud Data Services: Big Query, Dataflow, Dataproc
    – Azure: Data Lake, Synapse Analytics

  • Jupyter Notebooks
    – Setup and use of Jupyter Notebooks
    – Interactive records technology workflows
  • Version Control
    – Git and GitHub for collaborative paintings
    – Managing code repositories
  • Containerization
    – Introduction to Docker
    – Creating and dealing with Docker packing containers
  • Cloud Platforms
    – Deploying facts and technological know-how initiatives on AWS, Azure, and Google Cloud

  •  Project Planning
    – Defining the hassle and scope
    – Setting objectives
  • Data Collection and Preprocessing
    – Collecting records from numerous sources
    – Cleaning and getting ready information
  •  Model Building and Analysis
    – Applying gadget learning algorithms
    – Tuning and optimizing fashions
  • Result Presentation
    – Evaluating findings
    – Comprehensive reporting
    – User instructions
  • Effective Communication
    – Conveying statistics insights to non-technical audiences
  • Building a Portfolio
    – Documenting initiatives
    – Creating an internet presence (GitHub, LinkedIn)

  • Crafting an information technology resume
  •  Preparing for technical interviews
  •  General interview suggestions
  • Engaging with the statistics science network
  • Participating in workshops and seminars

Upcoming Batches

Enrolling in Data Scientist  courses in banagalore,Marathahalli can be a smart step toward career advancement. We offer free access to the BETA version of the services needed to create this data-driven content. The primary aim is to aid student engineers in perfecting their programming abilities with diverse Raspberry Pi devices and acquiring expertise in data collecting, combining, and analysing. Our instructions about the imminent BETA edition of the Selenium instrument in Web scraping, known as “Futuristic Automation,” are some of the tech-focused sessions available in scientific English Development carried out in an online¬ environment on a group screen equipped with internet connectivity points each consisting an R list. We grant entry for only one hour to specific items in the shopping centres to keep an eye on the security monitors managing the system.

Dates 

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16-09-2024

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23-09-2024

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21-09-2024

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28-09-2024

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About Data Science Trainer

Elegant IT Services’ data science training in bangalore, Instructor  Rajesh Kumar is the one in Marathahalli who delivers the Data Science courses. He is a data analytics, machine learning, and big data expert with 12 years of experience, and he can bring deep knowledge and the right perspective to the classroom. Nobody can deny that this book is very engaging and challenging. Anyone who wants to become an A+ student in data science will profit from his student-centered and engaging approach to teaching, which he’s so good at.

Data Science Certification

Elegant IT Services endorses the introduction to the project course on Data Scientist course in bangalore, marathahalli with certification . Expert trainers and state-of-the-art facilities are in Bangalore’s tech hub, a hub of IT courses to complete. Our Institute is the most popular destination for this project. Our innovative course, designed for beginners and experts, introduces the fundamental concepts and then takes students through more complex machine-learning techniques. Join us at Marathahalli to acquire the necessary capabilities to be a successful data scientist in the real world.

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Key Features of Data Science training in Marathahalli

Yes! Here are the basic training habits:
Expert-Driven Guidance: Teaches led by experts with rich experience in data science and analytics.

Advanced Courses: This course involves many subjects, such as statistical analysis, machine learning algorithms, and data visualization techniques.

Hands-On Learning: These activities are the ones that students should do to work out the steps, and the projects are the ones whose outcomes make students interact with the AI, and, thus, a real-life-like simulation of the problems one has to handle are done in a manner where students are actively engaged. Join data science training near me at Elegant IT Services. 

Flexible Learning Options: Offering courses with a schedule that’s adjustable to one’s needs and/or learning at one’s own pace are the options to suit every learner and to avoid any learning style conflict.

Career Guidance: Help in effective career planning, correct resume building, and interview preparation to enable them to do well in the areas of data science in which they get involved. These projects require collaboration and project management, which effectively applies the disciplines.

Modern Facilities: Modern training facilities with the latest technology.

Networking Opportunities: Easily recruit a group of peers, alumni, and industry professionals to network and collaborate.

Certification: Data science training in bangalore, provides Certification recognized upon completion of a course serves as a certificate of proficiency in data and enhances career prospects.

Project Mentoring: A guiding hand is the mentor’s care skill development and confidence in the data analyst role.

Continuous Learning: Furthermore, stable, long-lasting nursing could be accomplished by conducting workshops, seminars, and updated versions of our courses based on industry trends.

These aspects are illustrated by the comprehensive and supportive learning environment that Elegant IT Services in Marathahalli provides for those eager data science professionals.

Data Science Training Options

Classroom Training

  • Interactive and engaging classroom sessions
  • Hands-on training approximately 40 hours
  • Five scheduled interviews to be conducted
  • Modern classroom facilities
  • Job placement dedicated
  • The course is taught by experts in the field
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Online Training

10% Discount
  • An online interactive training
  • Hands-on training over 40 hours
  • Working professionals as speakers
  • Access to recordings for 1 year
  • Placements guarantee program
  • Minimum of 20 interviews guaranteed
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Corporate Training

  • Flexible pricing and billing options
  • Private cohorts are available with us
  • Training progress dashboards
  • Skills assessment and benchmarking
  • Integration capabilities with platform
  • Customer success manager
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FAQ

What is Data Science course in bangalore, and Why is it Important?

Data science course in bangalore  involves using various methods and tools to find insights and knowledge from data. It allows one to make informed decisions, predict trends, and optimize processes.

Who can benefit from training in Data Science training in bangalore, Elegant IT Services?

Anyone who wishes to work with data for meaningful interpretations may take advantage of such courses. These could be IT professionals, statisticians, business analysts, and others in these fields. You can also attend for data sceince online training.

How do program teaching skills differ regarding syllabus content offered during study hours per week, etc?

Usually, programming languages such as Python or R form part of the coursework. At the same time, statistical analysis and machine learning algorithms/data visualization tools like SQL & Hadoop also feature prominently. Combined, they are referred to as ‘Big Data’ tools and thus become key areas covered by any good data science training program.

 

What is data science training? Will it help my career?

Companies are looking for people who can turn data into insights, but more professionals are needed in this field. You can train to become a data scientist, suitable for various industries – finance, healthcare, retail and technology.

 

Do I need any programming knowledge before starting my studies in data science?

Although some courses may be described as introductory, they still provide valuable information even if you have yet to gain experience. One of the key stages here is developing coding skills, starting from the “hello world” level of complexity up to more advanced tasks like building machine learning models.

What are my chances after completing the Training?

Upon graduation from such programs, students might apply for jobs related to business analytics, predictive modelling or even artificial intelligence development. The need for specialists who can work with big databases has grown incredibly fast recently, so there will always be a demand for qualified data scientists worldwide.

 

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