bangalore
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https://www.eventshigh.com/detail/delhi/719e146bf4081d3933d5cb6ea4a1aa28-data-science-and-machine-learning

Data Science and Machine Learning Training

28.4852953,77.07469939999999
By Foito
Sat, 28 Mar 10:00AM - 3:00PM
Live Virtual Classroom , gurgaon
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Rs 30000
144 people viewed this event.

Pricing & Offers

Pricing & Offers
Zero convenience fee, ticket price shown below is the final price.
Sat, 28 Mar
, 10:00AM
- 3:00PM
Upto 2 Person (Online)
Live Instructor Led Online Screen Sharing Session
₹ 30,000
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Details

Details

NOTE: Our training sessions are conducted on a 1-2-1 basis (batches are not formed) as our workshops are tailor-made to your specific problem statement.

About the workshop:

As we pace into the era of Artificial Intelligence, Data Science is bound to become one of the most essential skills and getting to learn the industry applications of big data directly from an Industry Expert is no less than a Golden Opportunity.

Attending this workshop will make you familiar with data science and machine learning concepts and their practical applicability across various industries from scratch. This is a month-long course designed to give the maximum detailed exposure possible to all data science enthusiasts who wish to hone their skills under the direct guidance of Industry Experts. The training module has been fastidiously structured with an aim to aid all your concerns related to this ever-growing domain of Data Science.

The course below can be further channelized to a specific industry as per the requirement of the client.

Total Duration of Training: One Month

Topics Covered:

  • Python Programming- Python Basics, Indentation, Case Sensitive

  • Data Types- Integer, Float, String, Boolean, List, Tuple, Dictionary, Set, Series(Pandas), DataFrame(Pandas), Array(Numpy)

  • Functions and Classes- Classes, Function, Lambda, Map, Filter, Reduce, Zip

  • Errors and Exception Handling- Errors, System Defined Exception, User-Defined Exception

  • Loops and Conditional- If-else, While, For, Continue, Break, Pass

  • Advanced Python- List Comprehension, Dictionary Comprehension

  • Packages- Numpy, Pandas, Matplotlib, Seaborn, Stats and Math, Sklearn

  • Introduction to Machine Learning

  • Types of Data- Supervised, Unsupervised, Reinforcement

  • Basic Data Preparation- Data Cleaning, Handling Null Data

  • Statistics- Measure of Central Tendency, Skewness, Kurtosis, Hypothesis Testing, Baye's Theorem, Markov's Chain, etc

  • Applied Maths- PnC, Probability, Gaussian Distribution, Binomial Distributions, Poisson Distributions, Multivariate Gaussian Distributions

  • Linear Algebra- Linear Equation, Polynomial Equation

  • Time Series Models- ARIMA, Dickey-Fuller Test

  • Regression- Linear, Univariate, Multivariate, Polynomial

  • Clustering- K-means, Anamoly detection

  • Ensemble Learning- Random Forest

  • Advanced-Data Preparation- Data Cleaning, Normalization, Gradient Descent, Cost Function

  • Reinforcement- Q-Learning, MDP, Bellman Equation

  • Evaluation Metrics- Confusion Matrix, ROC-AUC Curve, R2 score, F-1 score, Mean Square Error

  • Dimension Reduction- Dimension Reduction, PCA

  • Optimization, Advanced Models and Framework- Neutral Network, Tensorflow
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Map & Directions

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Live Virtual Classroom Gurugram, Haryana 122008, India
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