Data Science Bootcamp - APG Learning
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Data Science Bootcamp

APG Learning began operations in 2013 with a mission to upskill and educate students and ensure a sustainable socio economic development. We run some of the most successful employability-related courses in the fields of agriculture, media, acting and allied subjects.…

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Course Detail

Format:

Full Time

Duration:

1 Year

Accreditation:

TISS SVE

Course Provider:

APG Learning

Start Date:

01 August 2019

Fees:

₹1,75,000/-

Duration

15 Days

Modules

7

Hours

100

Start Date

02 Nov 2019

Course Provider:

APG Learning

26,500.00 30,000.00

Address:Sakal Nagar,

Gate No. 1, Baner Road,

Aundh, Pune 411 007

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About Course

APG Learning began operations in 2013 with a mission to upskill and educate students and ensure a sustainable socio economic development. We run some of the most successful employability-related courses in the fields of agriculture, media, acting and allied subjects. At APG Learning, we aspire to uplift the community by empowering everyone to effortlessly access quality education.



With an alumni of over 1,00,000+ worldwide and successfully conducting hundreds of short term programs, workshops, seminars, and long term courses, we have entered the online segment to expand our reach and deliver courses for a wide range of audience comprised of entrepreneurs, leaders, corporate professionals, businessmen, farmers, students, etc. We combine practical experiences with academic knowledge in our teaching methods so that learning becomes fun and effective. Since balance is the key, we bridge the gap between conventional academic programs and present day methods to create a stable learning environment that has the goodness of both the worlds.



Objective:



  • Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.


  • However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.


  • For a good career growth with better pay Data Science is essential to study.

Modules

Part 1: Introduction

  • The Field of Data Science – The Various Data Science Disciplines
  • The Field of Data Science – Connecting the Data Science Disciplines
  • The Field of Data Science – The Benefits of Each Discipline
  • The Field of Data Science – Popular Data Science Techniques
  • The Field of Data Science – Popular Data Science Tools
  • The Field of Data Science – Careers in Data Science
  • The Field of Data Science – Debunking Common Misconceptions

Part 2: Probability

  • Combinatorics
  • Bayesian Inference
  • Probability Distributions
  • Probability in Other Fields

Part 3: Statistics

  • Statistics – Descriptive Statistics
  • Statistics – Practical Example: Descriptive Statistics
  • Statistics – Inferential Statistics Fundamentals
  • Statistics – Inferential Statistics: Confidence Intervals
  • Statistics – Practical Example: Inferential Statistics
  • Statistics – Hypothesis Testing
  • Statistics – Practical Example: Hypothesis Testing

Part 4: Introduction to Python

  • Python – Variables and Data Types
  • Python – Basic Python Syntax
  • Python – Other Python Operators
  • Python – Conditional Statements
  • Python – Python Functions
  • Python – Sequences
  • Python – Iterations
  • Python – Advanced Python Tools

Part 5: Advanced Statistical Methods in Python

  • Advanced Statistical Methods – Linear regression with StatsModels
  • Advanced Statistical Methods – Multiple Linear Regression with StatsModels
  • Advanced Statistical Methods – Linear Regression with sklearn
  • Advanced Statistical Methods – Practical Example: Linear Regression
  • Advanced Statistical Methods – Logistic Regression
  • Advanced Statistical Methods – Cluster Analysis
  • Advanced Statistical Methods – K-Means Clustering
  • Advanced Statistical Methods – Other Types of Clustering

Part 6: Mathematics

Part 7: Deep Learning with Neural Networks/ NLP

  • Deep Learning – Introduction to Neural Networks
  • Deep Learning – How to Build a Neural Network from Scratch with NumPy
  • Deep Learning – TensorFlow 2.0: Introduction
  • Deep Learning – Digging Deeper into NNs: Introducing Deep Neural Networks
  • Deep Learning – Overfitting
  • Deep Learning – Initialization
  • Deep Learning – Digging into Gradient Descent and Learning Rate Schedules
  • Deep Learning – Preprocessing
  • Deep Learning – Classifying on the MNIST Dataset
  • Deep Learning – Business Case Example
  • Deep Learning – Conclusion
  • Appendix: Deep Learning – TensorFlow 1: Introduction
  • Appendix: Deep Learning – TensorFlow 1: Classifying on the MNIST Dataset
  • Appendix: Deep Learning – TensorFlow 1: Business Case
  • Software Integration

 

Learning Outcomes

  • The course provides the entire toolbox you need to become a data scientist
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Impress interviewers by showing an understanding of the data science field
  • Learn how to pre-process data
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Start coding in Python and learn how to use it for statistical analysis
  • Perform linear and logistic regressions in Python
  • Carry out cluster and factor analysis
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Apply your skills to real-life business cases
  • Use state-of-the-art Deep Learning frameworks such as Google’s Tensor Flow Develop a business intuition while coding and solving tasks with big data
  • Unfold the power of deep neural networks
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations.

 

Deliverables:

  • Training by experienced trainer
  • 5 real life industry based projects in various domains by subject matter expert expert
  • Interactive & hands-on learning

Who Should Attend

  • You should take this course if you want to become a Data Scientist or if you want to learn about the field
  • This course is for you if you want a great career
  • The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

 

Fee Structure

Fees: 26500 + GST

Time: 9.30am-4.30pm

Registration details:

Call: 9372260000 / Email: contact@apglearning.in

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