End to End Data Science 2021-04-06T17:02:17+00:00

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End to End Data Science

This course includes the concepts and insight practical approach of Data Science and the learners will get to work in the areas of Machine learning, Deep Learning. A full-fledged course for working professionals and mentoring till they become data scientist.

Download Course Features
Video-Course Description

Key Features

  • Gain experience with handson exercises

  • Instructor led training

  • Flexibility of learning in class or online

  • Industry exposure – Use Cases

  • Learn by doing – Assignments, Tasks

  • Industry-relevant curriculum

  • Innovative Approach – Discussions, Quiz, webinar

  • Project Based Learning Approach

  • Capstone Projects

  • Solutions for your skill gaps

  • Upskilling and Level Setting

  • Dedicating mentoring sessions from industry experts

  • Career Support

  • Industry valued Certificate

Talk to an Expert

Schedule a meet with AI consultant to know more about the course, and the discussion will help to take action over learning.

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Schedule – Online (Live) Instructor Led Training

BatchScheduleCourse Fee
Open [One – One]FlexibleINR 125000

USD 1675

EURO 1500


** For payment and installment options, please contact +91 9841557655 **

Prerequisite : None


  • Introduction, Installing Python, Anaconda environment
  • Variables , Input Functions
  • Operators, Control Flow
  • String Handling
  • Data Structures-Lists, Tuples, Sets, Dictionary
  • Functions, Modules, Packages,
  • File Handling
  • Exception Handling
  • Object Oriented Paradigms
  • Numpy: Introduction, Numerical operations on Numpy
  • Pandas: Getting started with pandas
  • Data Frame Basics, Key Operations on Data Frames
  • Sci-py: working with Scipy
  • Scatter Plot, Line Chart, Histogram
  • Bar Chart, Box plot, Heat Map
  • Pair plot, scatter Matrix using Matplotlib
  • Pandas Vizualization
  • Seaborn
  • Working with Different File formats – CSV,JSON, PDF,binary format, HDF5
  • Interacting with data in Sql-Pysql with MysqlDB
  • Interacting with data in Nosql -pymongo with MongoDB
  • HDFS installation
  • HDFS Overview & Data storage
  • Get the data into Hadoop from local machine(Data Loading ) – vice versa
  • Map Reduce model
  • Hive and Pig model
  • Spark installation
  • Spark streaming
  • Pydoop and Pyspark implementation
  • Descriptive Statistics: Measuring central tendancy, Variance
  • Inferential Statistics : Hypothesis Test- P test, t test, z-score, Chi square test, ANOVA
  • Probability Distributions: Gaussian, Poisson, Bernouli, Binomial, Uniform, Exponential
  • Linear Algebra
  • Analytic Geometry
  • Matrix Decompositions
  • Vector Calculus
  • Continuous Optimization
  • Time Series, Down sampling,
  • Resampling, Upsampling
  • Time deltas, Time series forecasting with ARIMA
  • Multivariate Time Series
  • Getting Started with Data Mining
  • Data Cleaning / Wrangling
  • Exploratory Data Analysis
  • Affinity analysis,
  • Prediction Analysis
  • Scikit-Learn, Prepossessing
  • Fundamentals of Machine learning
  • Supervised Learning ,Unsupervised Learning
  • Regression,Classification and Clustering Problems
  • Various algorithms involved in machine learning problems
  • Regularization Techniques, Cross Validation, Evaluation Metrics
  • Dimensionality Reduction techniques
  • Market Basket Analysis, Recommender Systems
  • Getting started with TensorFlow
  • Loading and exploring the data
  • Data transformation & Data segmentation
  • Tensor and matrix operations
  • Computational graphs
  • Data pipelines
  • Dataset framework & manipulations
  • Loading data for classifiers
  • Extracting data, loss function
  • Optimization, accuracy
  • Model training using TensorFlow
  • Neural Networks Foundations
  • Fundamentals of deep learning
  • Activation Function
  • Hidden layers, hidden units
  • Illustrate & Training a Perceptron
  • Important Parameters of Perceptron
  • Various neural networks involved in deep learning
  • Creating a sequence of layers and adding layers in Tensorflow and Keras
  • Deep Learning with MLP
  • Regression networks
  • Auto encoders
  • Generative Adversarial Networks
  • Deep reinforcement learning, Q learning
  • Compile model by specifying functions & optimizers
  • Execution of the defined model using Tensor flow & Keras
  • Parameters vs Hyper parameter
  • Hyper parameter tuning
  • Regularization
  • Optimization
  • Policy Gradient Methods
  • Creating performant apps for ML models StreamLit &
  • Deploy Machine Learning Models’ dashboard using Joblib, Pickle & StreamLit
  • Deploying Streamlit Application in Heroku cloud- PaaS
  • Capstone Project – 1
  • Capstone Project – 2
  • Capstone Project – 3

Tools Covered

Streamlit tool


Instructor-led online training is an interactive mode of training. The trainer and learner(s) log in at the same time and live sessions will be done. NO RECORDED VIDEOS. Trainer will be interacting with learners in all sessions throughout the course/training.

All the modules and topics of this course are delivered through live scheduled sessions by the trainers. NO SELF – PACED VIDEOS.

VYOAM supports learners with its learning manage system, in addition with sharing the required materials, data tales and notes. Also the trainers will help you to get it done with the missed session.

Naïve learners with respect to programming and data science can very much take up this course. This program is designed to impart data science skills from scratch. This course will start from basics of Python programming.

NO PRE REQUISITE. However it is expected to have logical thinking, problem solving skills in addition with commitment.

Our trainers are part of Product Development and Consultancy division of VYOAM. They are highly qualified (PhD holders in Artificial Intelligence), AI Experts with years of relevant industrial experience. Our trainers are good at translating highly technical information in ways that others can understand in order to influence the effective knowledge transfer..

Mentors help the learners to set their target learning goals and discuss how to achieve them. Mentors also answer subject experts; provide feedback on projects, and help the learners to build their portfolio in data science domain.

Yes. Mentor ship is integrated part of this course. Learners can interact and get career assistance from mentors.

After successful completion of assignments, case studies, capstone projects thereby completion of course, learners will be provided with the certificate.

The fees can be paid in 3 0r 4 instalments. For more details about payment options and instalments, please contact +91 9841557655.

Yes. There is a group discount. Group discount is offered when you join as a group (3 members in a group)

Data science professionals has been listed the number one job by Glassdoor and a authentic statistics reports that the growth of data science needs will create 11.5 million job opportunities by 2026. Not only is there a huge need, but there is also a remarkable deficiency of qualified data professionals.  @ VYOAM, learners will be supported by not only referring to our clients against demand, but also supports the learner till they land in their dream job in data science domain. VYOAM offers training model that up-skill/re-skill the learner, which in turn makes the learner fully competitive and qualified data professional.

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