Data Science Training by Industry Experts

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Our Training Process

Data Science - Syllabus, Fees & Duration

MODULE 1

  • The Data Science Process
  • Apply the CRISP-DM process to business applications
  • Wrangle, explore, and analyze a dataset
  • Apply machine learning for prediction
  • Apply statistics for descriptive and inferential understanding
  • Draw conclusions that motivate others to act on your results

MODULE 2

  • Communicating with Stakeholders
  • Implement best practices in sharing your code and written summaries
  • Learn what makes a great data science blog
  • Learn how to create your ideas with the data science community

MODULE 3

  • Software Engineering Practices
  • Write clean, modular, and well-documented code
  • Refactor code for efficiency
  • Create unit tests to test programs
  • Write useful programs in multiple scripts
  • Track actions and results of processes with logging
  • Conduct and receive code reviews

MODULE 4

  • Object Oriented Programming
  • Understand when to use object oriented programming
  • Build and use classes
  • Understand magic methods
  • Write programs that include multiple classes, and follow good code structure
  • Learn how large, modular Python packages, such as pandas and scikit-learn, use object oriented programming
  • Portfolio Exercise: Build your own Python package

MODULE 5

  • Web Development
  • Learn about the components of a web app
  • Build a web application that uses Flask, Plotly, and the Bootstrap framework
  • Portfolio Exercise: Build a data dashboard using a dataset of your choice and deploy it to a web application

MODULE 6

  • ETL Pipelines
  • Understand what ETL pipelines are
  • Access and combine data from CSV, JSON, logs, APIs, and databases
  • Standardize encodings and columns
  • Normalize data and create dummy variables
  • Handle outliers, missing values, and duplicated data
  • Engineer new features by running calculations • Build a SQLite database to store cleaned data

MODULE 7

  • Natural Language Processing
  • Prepare text data for analysis with tokenization, lemmatization, and removing stop words
  • Use scikit-learn to transform and vectorize text data
  • Build features with bag of words and tf-idf
  • Extract features with tools such as named entity recognition and part of speech tagging
  • Build an NLP model to perform sentiment analysis

MODULE 8

  • Machine Learning Pipelines
  • Understand the advantages of using machine learning pipelines to streamline the data preparation and modeling process
  • Chain data transformations and an estimator with scikit- learn’s Pipeline
  • Use feature unions to perform steps in parallel and create more complex workflows
  • Grid search over pipeline to optimize parameters for entire workflow
  • Complete a case study to build a full machine learning pipeline that prepares data and creates a model for a dataset

MODULE 9

  • Experiment Design
  • Understand how to set up an experiment, and the ideas associated with experiments vs. observational studies
  • Defining control and test conditions
  • Choosing control and testing groups

MODULE 10

  • Statistical Concerns of Experimentation
  • Applications of statistics in the real world
  • Establishing key metrics
  • SMART experiments: Specific, Measurable, Actionable, Realistic, Timely

MODULE 11

  • A/B Testing
  • How it works and its limitations
  • Sources of Bias: Novelty and Recency Effects
  • Multiple Comparison Techniques (FDR, Bonferroni, Tukey)
  • Portfolio Exercise: Using a technical screener from Starbucks to analyze the results of an experiment and write up your findings

MODULE 12

  • Introduction to Recommendation Engines
  • Distinguish between common techniques for creating recommendation engines including knowledge based, content based, and collaborative filtering based methods.
  • Implement each of these techniques in python.
  • List business goals associated with recommendation engines, and be able to recognize which of these goals are most easily met with existing recommendation techniques.

MODULE 13

  • Matrix Factorization for Recommendations
  • Understand the pitfalls of traditional methods and pitfalls of measuring the influence of recommendation engines under traditional regression and classification techniques.
  • Create recommendation engines using matrix factorization and FunkSVD
  • Interpret the results of matrix factorization to better understand latent features of customer data
  • Determine common pitfalls of recommendation engines like the cold start problem and difficulties associated with usual tactics for assessing the effectiveness of recommendation engines using usual techniques, and potential solutions.

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Data Science Jobs in Chennai

Enjoy the demand

Find jobs related to Data Science in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Chennai, chennai and europe countries. You can find many jobs for freshers related to the job positions in Chennai.

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Storyteller
  • Machine Learning Scientist
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Database Administrator
  • ML Engineer
  • Computer Vision Engineer
Data Science internship jobs in Chennai

Data Science Internship/Course Details

Data Science You'll have a personal mentor who will keep track of your development.A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. The top Data Science course online for professionals who wish to expand their knowledge base and start a career in this industry is NESTSOFT in Chennai. You'll have a personal mentor who will keep track of your development. Effectively analyze both organized and unstructured data Create strategies to address company issues. Creative thinking, problem-solving skills, curiosity, and a drive to learn about and investigate industry trends and development, as well as teamwork, are among the soft skills required by data scientists. This finest Data Science course was built with the needs of businesses in mind when it comes to the field of Data Science. .

Success Stories

The enviable salary packages and track record of our previous students are the proof of our excellence. Please go through our students' reviews about our training methods and faculty and compare it to the recorded video classes that most of the other institutes offer. See for yourself how TechnoMaster is truly unique.

List of Training Institutes / Companies in Chennai

    Web Design Companies in Chennai

    1. Intrepid IT Services Address: 5E, kencers towers,, no 1, ramakrishna street, T.nagar, Chennai, Tamil Nadu 600017 Phone: 044 4541 0606 , website:www.intrepiditservices.com/
    2. SIS Training Institute Address: Old No- 36/1, New No- 18/1, 12th Avenue, Vaigai colony 1st cross street, Ashok Nagar, Chennai, Tamil Nadu 600083 Phone: 044 2471 7182 , website:https://www.indiamart.com/sis-institutes-ndt/services.html
    3. Hi-Tech Company Software Solution Chennai Private Limited Address: No4, 4th Street, Chennai, Bharathy Nagar, T Nagar, Chennai, Tamil Nadu 600017 Phone: 044 2834 4782 , website:htssindia.in/
    4. DSRC Address: 11 Smith Road, Kasturi Towers, Chennai, Tamil Nadu 600002 Phone: 044 4510 5000 , website:www.dsrc.com/
    5. Infiniti Software Solutions Address: 1st Floor, Mount Casa Blanca,, 260, Anna Salai, Mount Road., Chennai, Tamil Nadu 600006 Phone: 044 4343 8999 , website:infinitisoftware.net/
 courses in Chennai
This city encourages all types of development, each modern technology and the traditional arts and crafts, and embraces a series of paradoxes. chennai has flourished into a charming and welcoming city, in a time span of just over 350 years. Sprawled over a neighborhood of 200 sq. The city is the gateway to the rest of South India. And, it's also considered because the cultural hub of South India that is known for its affluent heritage in classical dance, music, architecture, sculpture, crafts, etc. And, it's also considered because the cultural hub of South India that is known for its affluent heritage in classical dance, music, architecture, sculpture, crafts, etc. .

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