Data Science Training by Experts

;

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.

Download Syllabus - Data Science
Course Fees
10000+
20+
50+
25+

Data Science Jobs in Philadelphia

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 Philadelphia, chennai and europe countries. You can find many jobs for freshers related to the job positions in Philadelphia.

  • 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/Course Details

Data Science internship jobs in Philadelphia
Data Science 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 Philadelphia. To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. Effectively analyze both organized and unstructured data Create strategies to address company issues. Cleaning and validating data to ensure that it is accurate and consistent. Data Science provides a diverse set of tools for analyzing data from a range of sources, including financial records, multimedia files, marketing forms, sensors, and text files. Today's Data Scientists must possess a wide range of abilities, including the ability to work with large amounts of data, parse that data, and translate it into an easily comprehensible format from which business insights may be drawn. Experts provide immersive online instructor-led seminars. This finest Data Science course was built with the needs of businesses in mind when it comes to the field of Data Science. You may learn all of the skills and talents required to become a data scientist by enrolling in the top data science online courses in Philadelphia. A Data Scientist is a highly skilled someone with advanced mathematical, statistical, scientific, analytical, and technical abilities who can prepare, clean, and validate organized and unstructured data for industries to utilize in making better decisions.

List of All Courses & Internship by TechnoMaster

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 Philadelphia

Teachers battle to keep order and field of their school rooms, in which enrollments of 30 or extra college students are commonplace. • Founded in 1791 through Reverend Richard Allen, Mother Bethel Church is the world`s first African Methodist Episcopal Church, and became on the middle of the nation`s Underground Railroad activity. Alexander Milne Calder created the William Penn statue atop City Hall, his son Alexander Stirling Calder designed the Swann Fountain on Logan Circle, and grandson Alexander`s mobiles grace the Philadelphia Museum of Art. PAEP is housed withinside the Graduate Art Education Department on the University of the Arts and, as such, will offer complete get entry to to the department`s sources such as present day artwork school rooms and studios, exhibition space, and the highbrow capital of its esteemed school who will function formal and informal specialists to the program. By operating with a partnership of extra than a hundred coaching artists representing all arts disciplines and eighty three arts and cultural organizations, PAEP will installation its sources in carrier to the faculty youngsters of Philadelphia. • Ft. • The Academy of Natural Sciences homes Lewis & Clark`s herbarium, which incorporates 2 hundred specimens located through the Lewis & Clark expedition. While research (see Appendix A, Reference List) affirms that arts training correlates definitely with fostering advanced scholar overall performance in all of those factors, there was a records on the SDP of discounts in staffing and humanities programming, and an opening in carrier delivery. Mifflin is the oldest fortification constantly in use withinside the U. • Freedom Theater, based in 1966, is certainly considered one among the nation`s OLDEST and biggest African-American theater agencies.

Trained more than 10000+ students who trust Nestsoft TechnoMaster

Get Your Personal Trainer