Data Science Specialization
This is a comprehensive online instructor led course that prepares you for various skillsets required in a Data Scientist profile that include Statistics, Tools and Business Skills. It covers entire data science pipeline from Data gathering, Data Manipulation, Exploratory Data Analysis, Model Planning, Model Building, Machine Learning algorithms and Data Visualization using tools like Python, Excel, Tableau and SQL.
- Exploratory Data Analysis and Statistics
- In-depth understanding of Python
- Data Visualization with Tableau
- Data Modelling and Model Evaluation using various Machine Learning Algorithms
- Instructor led online LIVE session for entire course duration
- Small batch size– Personalized attention
- Highly Interactive sessions (Two way participation – Chat and Speech)
- Highly experience and Qualified Trainers [Analytics experts, 10+ years industry experience (IITians)
- 20+ hours of In-depth case study discussion – Multiple domain Specific Projects
- Access to Session Recordings & Case studies thru Learning Manangement Portal for 2 years
- Career guidance and Placement Assistance
- Pay 5000/- during registration and rest only after experiencing 20 hours of sessions
- Course Completion Certification
- Highly approachable faculty – 24*7 support available
- Reattend LIVE sessions -If you miss a Lecture due to some reason
200 hours (25 weeks)
9:30 – 12:30 [Sat,Sun]
21:30 – 22:30 [Tue,Thu]
INR 45000 inc. Taxes
In this module, participants will be introduced to Descriptive and Inferential statistics concepts and implementation using real-world data will also be covered. It will end with a case study implementation of EDA.
- Statistics Fundamentals and Implementation
- Exploratory Data Analysis
- ESSENTIALS OF PYTHON PROGRAMMING
- BASIC DATA STRUCTURES AND FUNCTIONS IN PYTHON
- INTRODUCTION TO
-Matplotlib and Seaborn Library
- DATA EXPLORATION USING STATISTICS
Machine Learning algorithms are the backbone of Predictive Modelling. This is where the Crux of Data Science lies. The end objective of solving a data science problem is finding the patterns in the data and represent that in the form of a Data model. The algorithms taught in our course cover almost all of the problems data scientists solve on a regular basis.
- Introduction to Supervised and Unsupervised Learning
- Linear Regression with Multiple Variables
- Logistic Regression
- Decision Trees [CART]
- k-Fold Cross Validation
- Bagging and Bootstrapping
- Random Forest
- Gradient Boosting (XGBoost)
- Principal component Analysis
- K-means clustering
- Hierarchical Clustering
- Market Basket Analysis
- Support Vector Machine
- Naive Bayes
- Time Series Analysis
Big Data Analytics
With a shifting focus of industry on analyzing Big Data, this module will prepare
the students to do exactly that. The emphasis of the module will be on mastering Spark, which emerged as the most important big data processing framework. Beginning with the fundamentals and going on to building important concepts like Spark ML and Spark Streaming (to analyse streaming data).
Participants will gain the ability to initiate and design highly scalable systems that can accept, store and analyse large volumes of data in batch mode or real time.
- INTRODUCTION TO SPARK
- SPARK BASICS
- WORKING WITH RDDS IN SPARK
- SPARK SQL AND DATAFRAME
- SPARK CONFIGURATION, MONITORING AND TUNING
- SPARK STREAMING
- APPLYING MACHINE LEARNING ALGORITHMS
In this module, participants will learn the foundations of Deep Learning and understand how to build neural networks. The implementation of the same will be done using Python, TensorFlow and Keras.
- INTRODUCTION TO ARTIFICIAL NEURAL NETWORKS WITH KERAS
-From Biological to Artificial Neurons
-Implementing MLPs with Keras
-Fine-Tuning Neural Network Hyperparameters
- TRAINING DEEP NEURAL NETWORKS
-Vanishing/Exploding Gradients Problems
-Reusing Pretrained Layers
-Avoiding Overfitting Through Regularization
-Summary and Practical Guidelines
Data Visualization (Recorded)
Tableau is one of the most popular Data Visualization tools used by Data Science and Business Intelligence professionals. In fact, it has been the market leader in reporting tools for almost 10 years (Source: Gartner magic quadrant). Once the predictive analysis of data is done, data scientists generally use Tableau to send out the reports to business which can then take decisions accordingly.
- INTRO TO DATA VISUALIZATION AND TABLEAU
- DATA CONNECTIONS – JOINS AND VIZQL
- BUIDING BASIC CHARTS, CHART TYPES AND MAPPING
- AGGREGATION, PARAMETER
- STATISTICAL ANALYSIS USING TABLEAU – REGRESSION AND BOX PLOTS
- TABLE CALCULATION, CALCULATED FIELDS
- INTEGRATION OF R/PYTHON WITH TABLEAU
Structured query language (SQL) is the language of databases. Whether you run reports or provide a dynamic website, you need to know SQL to add, delete, edit and view records. Databases organize and collect your data, and the SQL language is the liaison between you and the data. This module provides a step-by-step overview and instructions that help you get started with the SQL language.
- INTRODUCTION TO SQL
- WHAT ARE RELATIONAL DATABASES
- ENTITY RELATIONSHIP DIAGRAMS AND RELATIONL SCHEMAS
- QUERIES TO RETRIEVE AND SORT DATA THAT MEET SPECIFIC CRITERIA
- SUMMARIZE ROWS OF DATA USING AGGREGATE FUNCTIONS
- SUB –QUERIES
- Personalized attention
- LIVE instructor-led training throughout the training duration
- Entirely Hands-On – Case Study based
- Practical Inputs from real-time scenarios
- Lifetime Access to Session Recordings
Kushagra, (IIT Delhi – 8+ years experience in Analytics & data science), has a keen interest in Problem Solving, Deriving insights & Improving the efficiency of processes with new age technologies.
He’s good with statistical concepts and possess thorough business understanding along with practical experience in linear models (like Linear Regression, Logistic Regression, Ridge Regression, Lasso Regression),
Tree based algorithms (like Decision trees, Bagging, Random Forest, GBM, XGBoost), clustering (like K-Means, Hierarchical),Time-series analysis (like ARMA, ARIMA, stationarity), Deep learning(CN, RNN), NLP Techniques(TFIDF, LDA, Topic Modelling) Extensive knowledge of Tools like R,Python, Spark, Tensorflow, Keras, Tableau. Trained 500+ participants in R, Machine Learning, Tableau and Python, Big Data Analytics at Dimensionless Conducted workshops and training on Data Analytics for Corporate and Colleges
HIMANSHU (IIT, Bombay – 10+ years experience in Data Science) A machine-learning practitioner, fascinated by the numerous application of Artificial Intelligence in the day to day life.
I enjoy applying my quantitative skills to new large-scale, data-intensive problems.I am an avid learner keen to be the frontrunner in the field of AI. I enjoy learning new technologies at work and strive hard to acquire finesse in skills that I have honed over my career.
Trained 500+ participants in R, Machine Learning, Tableau and Python, Big Data Analytics and Deep Learning at Dimensionless
Conducted workshops and training on Data Analytics for Corporate and Colleges
He possesses knowledge of a wide variety of machine learning and deep learning algorithms.
Why Should I Learn Data Science from Dimensionless?
Dimensionless Tech provides best online data science training that provides in-depth course coverage, case study based learning, entirely Hands-on driven sessions with Personalised attention to every participant. We guarantee Learning.
What Are The Various Modes Of Training That you Offer?
We provide only instructor-led LIVE online training sessions. We do not provide classroom trainings.
How is your online training better than classroom training?
In physical classrooms, students generally feel hesitant to ask questions. Unlike other online courses, we allow you to speak in the session and ask your doubts. The interactivity level is similar to classroom training and you get it at the comfort of your home. If you miss any class or didn’t understand some concepts, you can’t go through the class again. However, in online courses, it’s possible to do that. We share the recordings of all our classes after each class with the student. Also, there’s no hassle of long-distance commuting and disrupting your schedule.
Can I ask my doubts during the session?
All participants are encouraged to speak up and ask their doubts. We answer all the doubts with same sincerity.
Is there a hardware requirement for this course?
Any laptop with 2GB RAM and Windows 7 and above is perfectly fine for this course. For large data, the access will be given on the online lab.
What if I miss a session, due to some unavoidable situation?
We understand that while balancing your personal and professional commitments you might miss a session. Hence, all our sessions are recorded and the recordings are shared with you through our Learning Management Portal.
How long will I have access to the Learning Management Portal?
You will have lifetime access to the portal and you can view the Videos, Notes, Books, Assignments as many time
What Kind Of Projects Will I Be Working On As Part Of The Training?
During the training you will be solving multiple case studies from different domains. Once the LIVE training is done, you will start implementing your learnings on Real Time Datasets. You can work on data from various domains like Retail, Manufacturing, Supply Chain, Operations, Telecom, Oil and Gas and many more. You would be working on multiple projects so that you can gain enough content and confidence to enter into the field of Data Science.
Do You Provide Placement Assistance?
Yes, we provide you with real-time industry requirements on a daily basis through our connect in the industry. These requirements generally come through referral channels, hence the probability to get through increases manifold. The HR from the team, helps you with Resume Building and Interview Preparation as well.
Do I get a Course Completion Certificate?
Yes, we will be issuing a course completion certification to all individuals who successfully complete the training.