The Freedom Fast Track

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Deeplearningtrack – Learn Data Science Online with Industry Professionals


Starting soon


8 weeks (online weekend classes)




INR 35,000


INR 35,000






Course Eligibility: Basic working knowledge of at least one programming language.

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Deeplearningtrack Instructors

A group of analytics and data science professionals have recently launched an online data science school Deeplearningtrack  to bridge the gap between industry demand & candidate abilities. Through their online data science training school, they are offering online short duration instructor led courses in machine learning, programming and advanced topics like deep learning. They use an innovative teaching methodology where they teach the most complex concepts in a simplified manner through hands on sessions, case studies and unique tools like excel sheet demos of complex algorithms. Their aim is to quicken the process of learning through their course materials, pre-read hand-outs and codes, so that their students are ready to apply their knowledge from day one.

To help learners move from beginners to practitioners, they put together the following:

  • A faculty team from Amazon, ZS Associates, American Express along with industry veterans

  • Best in class content that teaches the most complex concepts in a simple manner

  • 15 case studies so that their students appreciate how to apply data science better & also to draw the maximum from their instructors’ experience

  • A quick but effective 8 weeks course curriculum while making sure that no concept is missed out through having put in hundreds of hours in preparing course material, pre-read handouts & software codes

    Week Topics Content
    1 Python Programming Includes basics as well as advanced topics on user defined functions, visualizations. Hands-on sessions with financial transaction dataset
    2 Statistics Statistical modelling including data preparation, model building, evaluation and advanced topics on distributions and hypothesis testing
    3 Regression Techniques like Linear, Logistic and generalized regression. Work on Kaggle data-sets and business case studies like customer contact rate forecast
    4 Classification Techniques Decision Trees, Ensemble methods like bagging(Random Forest), boosting (adaboost,GBM) while solving assignments on product classification and predicting customer default
    5 Neural networks Introduction to learning algorithms, Network architectures including concepts like feedforward nets, backpropagation
    6 Unsupervised learning Clustering – K means, PCA, Factor analysis; Recommender systems – Collaborative filtering, Matrix factorization. Assignments include claim, movie rating prediction
    7 Time-series Analysis Decomposing time series data, ARIMA models for forecasting problems like tourism, solar energy consumption
    8 Natural Language Processing Text pre-processing and sentiment analysis for product reviews. Model development for unstructured data with assignments on search relevance
    Guest Speaker Session Quick overview of various other case studies applied in industry by industry practitioners

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